data mining related thesis topics

82 Data Mining Essay Topic Ideas & Examples

🏆 best data mining topic ideas & essay examples, 💡 good essay topics on data mining, ✅ most interesting data mining topics to write about.

Data Mining Classifiers: The Advantages and Disadvantages One of the major disadvantages of this algorithm is the fact that it has to generate distance measures for all the recorded attributes.
Data Mining Role in Companies The increasing adoption of data mining in various sectors illustrates the potential of the technology regarding the analysis of data by entities that seek information crucial to their operations.
Data Mining in Social Networks: Linkedin.com One of the ways to achieve the aim is to understand how users view data mining of their data on LinkedIn.
Disadvantages of Using Web 2.0 for Data Mining Applications This data can be confusing to the readers and may not be reliable. Lastly, with the use of Web 2.
The Data Mining Method in Healthcare and Education Thus, I would use data mining in both cases; however, before that, I would discover a way to improve the algorithms used for it.
Data Mining Tools and Data Mining Myths The first problem is correlated with keeping the identity of the person evolved in data mining secret. One of the major myths regarding data mining is that it can replace domain knowledge.
Hybrid Data Mining Approach in Healthcare One of the healthcare projects that will call for the use of data mining is treatment evaluation. In this case, it is essential to realize that the main aim of health data mining is to […]
Terrorism and Data Mining Algorithms However, this is a necessary evil as the nation’s security has to be prioritized since these attacks lead to harm to a larger population compared to the infringements.
Transforming Coded and Text Data Before Data Mining However, to complete data mining, it is necessary to transform the data according to the techniques that are to be used in the process.
Data Mining and Machine Learning Algorithms The shortest distance of string between two instances defines the distance of measure. However, this is also not very clear as to which transformations are summed, and thus it aims to a probability with the […]
Summary of C4.5 Algorithm: Data Mining 5 algorism: Each record from set of data should be associated with one of the offered classes, it means that one of the attributes of the class should be considered as a class mark.
Ethnography and Data Mining in Anthropology The study of cultures is of great importance under normal circumstances to enhance the understanding of the same. Data mining is the success secret of ethnography.
Issues With Data Mining It is necessary to note that the usage of data mining helps FBI to have access to the necessary information for terrorism and crime tracking.
Large Volume Data Handling: An Efficient Data Mining Solution Data mining is the process of sorting huge amount of data and finding out the relevant data. Data mining is widely used for the maintenance of data which helps a lot to an organization in […]
Levi’s Company’s Data Mining & Customer Analytics Levi, the renowned name in jeans is feeling the heat of competition from a number of other brands, which have come upon the scene well after Levi’s but today appear to be approaching Levi’s market […]
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence This paper aims to review the application of A.I.in the context of blockchain finance by examining scholarly articles to determine whether the A.I.algorithm can be used to analyze this financial market.
“Data Mining and Customer Relationship Marketing in the Banking Industry“ by Chye & Gerry First of all, the article generally elaborates on the notion of customer relationship management, which is defined as “the process of predicting customer behavior and selecting actions to influence that behavior to benefit the company”.
Data Mining Techniques and Applications The use of data mining to detect disturbances in the ecosystem can help to avert problems that are destructive to the environment and to society.
Ethical Data Mining in the UAE Traffic Department The research question identified in the assignment two is considered to be the following, namely whether the implementation of the business intelligence into the working process will beneficially influence the work of the Traffic Department […]
Canadian University Dubai and Data Mining The aim of mining data in the education environment is to enhance the quality of education for the mass through proactive and knowledge-based decision-making approaches.
Data Mining and Customer Relationship Management As such, CRM not only entails the integration of marketing, sales, customer service, and supply chain capabilities of the firm to attain elevated efficiencies and effectiveness in conveying customer value, but it obliges the organization […]
E-Commerce: Mining Data for Better Business Intelligence The method allowed the use of Intel and an example to build the study and the literature on data mining for business intelligence to analyze the findings.
Ethical Implications of Data Mining by Government Institutions Critics of personal data mining insist that it infringes on the rights of an individual and result to the loss of sensitive information.
Data Warehouse and Data Mining in Business The circumstances leading to the establishment and development of the concept of data warehousing was attributed to the fact that failure to have a data warehouse led to the need of putting in place large […]
Data Mining: Concepts and Methods Speed of data mining process is important as it has a role to play in the relevance of the data mined. The accuracy of data is also another factor that can be used to measure […]
Data Mining Technologies According to Han & Kamber, data mining is the process of discovering correlations, patterns, trends or relationships by searching through a large amount of data that in most circumstances is stored in repositories, business databases […]
Data Mining: A Critical Discussion In recent times, the relatively new discipline of data mining has been a subject of widely published debate in mainstream forums and academic discourses, not only due to the fact that it forms a critical […]
Commercial Uses of Data Mining Data mining process entails the use of large relational database to identify the correlation that exists in a given data. The principal role of the applications is to sift the data to identify correlations.
A Discussion on the Acceptability of Data Mining Today, more than ever before, individuals, organizations and governments have access to seemingly endless amounts of data that has been stored electronically on the World Wide Web and the Internet, and thus it makes much […]
Applying Data Mining Technology for Insurance Rate Making: Automobile Insurance Example
Applebee’s, Travelocity and Others: Data Mining for Business Decisions
Applying Data Mining Procedures to a Customer Relationship
Business Intelligence as Competitive Tool of Data Mining
Overview of Accounting Information System Data Mining
Applying Data Mining Technique to Disassembly Sequence Planning
Approach for Image Data Mining Cultural Studies
Apriori Algorithm for the Data Mining of Global Cyberspace Security Issues
Database Data Mining: The Silent Invasion of Privacy
Data Management: Data Warehousing and Data Mining
Constructive Data Mining: Modeling Consumers’ Expenditure in Venezuela
Data Mining and Its Impact on Healthcare
Innovations and Perspectives in Data Mining and Knowledge Discovery
Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Linking Data Mining and Anomaly Detection Techniques
Data Mining and Pattern Recognition Models for Identifying Inherited Diseases
Credit Card Fraud Detection Through Data Mining
Data Mining Approach for Direct Marketing of Banking Products
Constructive Data Mining: Modeling Argentine Broad Money Demand
Data Mining-Based Dispatching System for Solving the Pickup and Delivery Problem
Commercially Available Data Mining Tools Used in the Economic Environment
Data Mining Climate Variability as an Indicator of U.S. Natural Gas
Analysis of Data Mining in the Pharmaceutical Industry
Data Mining-Driven Analysis and Decomposition in Agent Supply Chain Management Networks
Credit Evaluation Model for Banks Using Data Mining
Data Mining for Business Intelligence: Multiple Linear Regression
Cluster Analysis for Diabetic Retinopathy Prediction Using Data Mining Techniques
Data Mining for Fraud Detection Using Invoicing Data
Jaeger Uses Data Mining to Reduce Losses From Crime and Waste
Data Mining for Industrial Engineering and Management
Business Intelligence and Data Mining – Decision Trees
Data Mining for Traffic Prediction and Intelligent Traffic Management System
Building Data Mining Applications for CRM
Data Mining Optimization Algorithms Based on the Swarm Intelligence
Big Data Mining: Challenges, Technologies, Tools, and Applications
Data Mining Solutions for the Business Environment
Overview of Big Data Mining and Business Intelligence Trends
Data Mining Techniques for Customer Relationship Management
Classification-Based Data Mining Approach for Quality Control in Wine Production
Data Mining With Local Model Specification Uncertainty
Employing Data Mining Techniques in Testing the Effectiveness of Modernization Theory
Enhancing Information Management Through Data Mining Analytics
Evaluating Feature Selection Methods for Learning in Data Mining Applications
Extracting Formations From Long Financial Time Series Using Data Mining
Financial and Banking Markets and Data Mining Techniques
Fraudulent Financial Statements and Detection Through Techniques of Data Mining
Harmful Impact Internet and Data Mining Have on Society
Informatics, Data Mining, Econometrics, and Financial Economics: A Connection
Integrating Data Mining Techniques Into Telemedicine Systems
Investigating Tobacco Usage Habits Using Data Mining Approach
Electronics Engineering Paper Topics
Cyber Security Topics
Google Paper Topics
Hacking Essay Topics
Identity Theft Essay Ideas
Internet Research Ideas
Microsoft Topics
Chicago (A-D)
Chicago (N-B)

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105 Data Mining Essay Topic Ideas & Examples

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Data mining is a powerful tool that helps businesses and organizations uncover hidden patterns, trends, and insights from large datasets. It involves the process of extracting valuable information from raw data, which can then be used for various purposes such as improving decision-making, predicting future outcomes, and understanding customer behavior. If you are a student or a professional looking to write an essay on data mining, here are 105 topic ideas and examples to help you get started.

The importance of data mining in today's business world
Ethical considerations in data mining
The impact of data mining on privacy
How data mining is used in healthcare to improve patient outcomes
Predictive analytics: Using data mining to forecast future trends
Data mining techniques for fraud detection in financial institutions
The role of data mining in customer relationship management
The use of data mining in social media marketing
Data mining and its application in personalized advertising
The benefits of data mining in supply chain management
Text mining: Analyzing unstructured data to extract valuable insights
The challenges of big data mining
Data mining in e-commerce: Enhancing customer experience
The role of data mining in improving cybersecurity
Data mining and its impact on decision-making in organizations
The use of data mining in predicting stock market trends
Data mining and its role in recommendation systems
The benefits of data mining in the education sector
Data mining techniques for sentiment analysis
The ethical implications of data mining in government surveillance
Data mining in the gaming industry: Enhancing player experience
The role of data mining in personalized medicine
Data mining techniques for credit scoring and risk assessment
The use of data mining in sports analytics
Data mining and its impact on urban planning
Data mining and its role in weather forecasting
The challenges of data mining in social network analysis
Data mining techniques for detecting plagiarism in academic papers
Data mining and its application in predicting natural disasters
The role of data mining in improving transportation systems
Data mining and its impact on online dating platforms
Data mining for predicting customer churn in telecommunications industry
The use of data mining in optimizing energy consumption
Data mining techniques for detecting credit card fraud
Data mining and its role in personalized news recommendation
The benefits of data mining in human resources management
Data mining in healthcare for disease diagnosis and treatment
Data mining and its impact on online advertising
Data mining techniques for identifying patterns in gene expression data
The role of data mining in improving online learning platforms
Data mining and its application in criminal investigations
The use of data mining in optimizing manufacturing processes
Data mining techniques for predicting customer lifetime value
The benefits of data mining in predicting traffic congestion
Data mining and its role in predicting customer preferences
Data mining in environmental analysis and conservation efforts
Data mining and its impact on personalized financial planning
The challenges of data mining in healthcare data integration
Data mining techniques for analyzing social media sentiment
The role of data mining in improving public safety
Data mining and its application in fraud detection in insurance industry
The use of data mining in optimizing online search engines
Data mining techniques for predicting student performance in education
Data mining and its impact on improving online user experience
Data mining and its role in predicting customer satisfaction
The benefits of data mining in optimizing logistics and supply chain
Data mining in crime analysis and prevention
Data mining and its impact on personalization in online shopping
Data mining techniques for analyzing customer feedback and reviews
The role of data mining in improving healthcare resource allocation
Data mining and its application in predicting customer lifetime loyalty
The use of data mining in optimizing inventory management
Data mining techniques for detecting fraudulent insurance claims
Data mining and its role in predicting disease outbreaks
Data mining in sentiment analysis of political discourse
Data mining and its impact on improving online voting systems
The challenges of data mining in analyzing geospatial data
Data mining techniques for optimizing pricing strategies in retail
The benefits of data mining in predicting customer churn in telecom industry
Data mining and its role in improving road safety
Data mining and its application in predicting customer behavior
The use of data mining in optimizing energy distribution networks
Data mining techniques for detecting insider trading in financial markets
Data mining and its impact on personalized travel recommendations
Data mining and its role in predicting customer loyalty
The benefits of data mining in optimizing warehouse operations
Data mining in fraud detection and prevention in online transactions
Data mining and its impact on personalized healthcare recommendations
Data mining techniques for analyzing customer segmentation
The role of data mining in improving disaster response and recovery
Data mining and its application in predicting customer lifetime value
The use of data mining in optimizing fleet management
Data mining techniques for detecting money laundering activities
Data mining and its role in predicting customer preferences in online advertising
The benefits of data mining in optimizing service quality in hospitality industry
Data mining in predicting student dropout and improving retention
Data mining and its impact on personalized music recommendations
Data mining techniques for analyzing patterns in web usage data
The role of data mining in improving urban mobility and transportation systems
Data mining and its application in predicting customer satisfaction in retail
The use of data mining in optimizing healthcare resource allocation
Data mining techniques for detecting online identity theft
Data mining and its role in predicting customer lifetime loyalty in e-commerce
The benefits of data mining in optimizing delivery routes
Data mining in detecting patterns of online extremist behavior
Data mining and its impact on enhancing personalized learning experiences
Data mining techniques for analyzing customer churn in subscription-based services
The role of data mining in improving disaster risk reduction strategies
Data mining and its application in predicting customer behavior in online gaming
The use of data mining in optimizing maintenance schedules for industrial equipment
Data mining techniques for detecting healthcare fraud and abuse
Data mining and its role in predicting customer preferences in online travel booking
The benefits of data mining in optimizing waste management processes
Data mining in detecting patterns of cyberbullying behavior
Data mining and its impact on enhancing personalized financial advice

These topic ideas provide a wide range of options for your data mining essay. Whether you are interested in business applications, healthcare, social media, or any other field, there is a topic that suits your interests. Remember to choose a topic that you are passionate about and conduct thorough research to provide a well-informed and insightful essay on data mining.

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Distance Based Pattern Driven Mining for Outlier Detection in High Dimensional Big Dataset

Detection of outliers or anomalies is one of the vital issues in pattern-driven data mining. Outlier detection detects the inconsistent behavior of individual objects. It is an important sector in the data mining field with several different applications such as detecting credit card fraud, hacking discovery and discovering criminal activities. It is necessary to develop tools used to uncover the critical information established in the extensive data. This paper investigated a novel method for detecting cluster outliers in a multidimensional dataset, capable of identifying the clusters and outliers for datasets containing noise. The proposed method can detect the groups and outliers left by the clustering process, like instant irregular sets of clusters (C) and outliers (O), to boost the results. The results obtained after applying the algorithm to the dataset improved in terms of several parameters. For the comparative analysis, the accurate average value and the recall value parameters are computed. The accurate average value is 74.05% of the existing COID algorithm, and our proposed algorithm has 77.21%. The average recall value is 81.19% and 89.51% of the existing and proposed algorithm, which shows that the proposed work efficiency is better than the existing COID algorithm.

Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.

Multi-objective economic load dispatch method based on data mining technology for large coal-fired power plants

User activity classification and domain-wise ranking through social interactions.

Twitter has gained a significant prevalence among the users across the numerous domains, in the majority of the countries, and among different age groups. It servers a real-time micro-blogging service for communication and opinion sharing. Twitter is sharing its data for research and study purposes by exposing open APIs that make it the most suitable source of data for social media analytics. Applying data mining and machine learning techniques on tweets is gaining more and more interest. The most prominent enigma in social media analytics is to automatically identify and rank influencers. This research is aimed to detect the user's topics of interest in social media and rank them based on specific topics, domains, etc. Few hybrid parameters are also distinguished in this research based on the post's content, post’s metadata, user’s profile, and user's network feature to capture different aspects of being influential and used in the ranking algorithm. Results concluded that the proposed approach is well effective in both the classification and ranking of individuals in a cluster.

A data mining analysis of COVID-19 cases in states of United States of America

Epidemic diseases can be extremely dangerous with its hazarding influences. They may have negative effects on economies, businesses, environment, humans, and workforce. In this paper, some of the factors that are interrelated with COVID-19 pandemic have been examined using data mining methodologies and approaches. As a result of the analysis some rules and insights have been discovered and performances of the data mining algorithms have been evaluated. According to the analysis results, JRip algorithmic technique had the most correct classification rate and the lowest root mean squared error (RMSE). Considering classification rate and RMSE measure, JRip can be considered as an effective method in understanding factors that are related with corona virus caused deaths.

Exploring distributed energy generation for sustainable development: A data mining approach

A comprehensive guideline for bengali sentiment annotation.

Sentiment Analysis (SA) is a Natural Language Processing (NLP) and an Information Extraction (IE) task that primarily aims to obtain the writer’s feelings expressed in positive or negative by analyzing a large number of documents. SA is also widely studied in the fields of data mining, web mining, text mining, and information retrieval. The fundamental task in sentiment analysis is to classify the polarity of a given content as Positive, Negative, or Neutral . Although extensive research has been conducted in this area of computational linguistics, most of the research work has been carried out in the context of English language. However, Bengali sentiment expression has varying degree of sentiment labels, which can be plausibly distinct from English language. Therefore, sentiment assessment of Bengali language is undeniably important to be developed and executed properly. In sentiment analysis, the prediction potential of an automatic modeling is completely dependent on the quality of dataset annotation. Bengali sentiment annotation is a challenging task due to diversified structures (syntax) of the language and its different degrees of innate sentiments (i.e., weakly and strongly positive/negative sentiments). Thus, in this article, we propose a novel and precise guideline for the researchers, linguistic experts, and referees to annotate Bengali sentences immaculately with a view to building effective datasets for automatic sentiment prediction efficiently.

Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion modeling provides fundamental support for many downstream applications (e.g., public opinion monitoring, rumor source identification, and viral marketing). Tremendous efforts have been devoted to this area to understand and quantify information diffusion dynamics. This survey investigates and summarizes the emerging distinguished works in diffusion modeling. We first put forward a unified information diffusion concept in terms of three components: information, user decision, and social vectors, followed by a detailed introduction of the methodologies for diffusion modeling. And then, a new taxonomy adopting hybrid philosophy (i.e., granularity and techniques) is proposed, and we made a series of comparative studies on elementary diffusion models under our taxonomy from the aspects of assumptions, methods, and pros and cons. We further summarized representative diffusion modeling in special scenarios and significant downstream tasks based on these elementary models. Finally, open issues in this field following the methodology of diffusion modeling are discussed.

The Influence of E-book Teaching on the Motivation and Effectiveness of Learning Law by Using Data Mining Analysis

This paper studies the motivation of learning law, compares the teaching effectiveness of two different teaching methods, e-book teaching and traditional teaching, and analyses the influence of e-book teaching on the effectiveness of law by using big data analysis. From the perspective of law student psychology, e-book teaching can attract students' attention, stimulate students' interest in learning, deepen knowledge impression while learning, expand knowledge, and ultimately improve the performance of practical assessment. With a small sample size, there may be some deficiencies in the research results' representativeness. To stimulate the learning motivation of law as well as some other theoretical disciplines in colleges and universities has particular referential significance and provides ideas for the reform of teaching mode at colleges and universities. This paper uses a decision tree algorithm in data mining for the analysis and finds out the influencing factors of law students' learning motivation and effectiveness in the learning process from students' perspective.

Intelligent Data Mining based Method for Efficient English Teaching and Cultural Analysis

The emergence of online education helps improving the traditional English teaching quality greatly. However, it only moves the teaching process from offline to online, which does not really change the essence of traditional English teaching. In this work, we mainly study an intelligent English teaching method to further improve the quality of English teaching. Specifically, the random forest is firstly used to analyze and excavate the grammatical and syntactic features of the English text. Then, the decision tree based method is proposed to make a prediction about the English text in terms of its grammar or syntax issues. The evaluation results indicate that the proposed method can effectively improve the accuracy of English grammar or syntax recognition.

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Data Mining Dissertation Topics

The term “data mining” refers to an intelligent data lookup capacity that uses statistics-based algorithms and methodologies to find trends, patterns, links, and correlations within the collected data and records. Audio, Pictorial, Video, textual, online, and social media-based mining are only a few examples of data mining. This article will provide you with a complete overview of various recent data mining dissertation topics . Let us first start with the definition of data mining processes.

What is the data mining process?

The practice of evaluating a huge batch containing data to find different patterns is known as data mining.
Companies can utilize data mining for a variety of purposes, including knowing as to what consumers are engaged in or would like to buy, as well as detection of fraudulent activities and malware scanning.

Hence data mining plays a very significant role in both commercial and personal life aspects of the modern world. We have been working on data mining dissertation topics and project ideas for more than 15 years as a result of which we have gained huge expertise and have acquired vast knowledge, skills, and experience in the field. So we can guide you in all the existing and normal data mining methods and techniques. Let us now talk about the data mining techniques below

Data mining techniques

Neural networks
Rule induction
Nearest neighbor classification
Decision tree
Descriptive techniques – sequential analysis, association, and clustering

Complete explanation and description on all these techniques and methods are available at our website on data mining dissertation topics . By understanding the importance of data mining, we have successfully worked out several advanced projects and implementations in real-time . Check out our website for all details about our successful projects in data mining. Let us now see about the data mining approaches below

Approaches in data mining

Belief nets
Neural nets (Kohonen and backpropagation)
Decision trees (CHAID, CAITT, and C 4.5)
Rules (genetic algorithms and induction)
Case-based reasoning
Nearest neighbor

This is the basic classification of the various data mining approaches that are in use today. With the support of the best engineers and world-class certified experts in data mining , we are here to provide you with a massive amount of reliable and authentic research data along with complete support in interpretation, analysis, and understanding them . Get in touch with us at any time for complete support for your data mining dissertation . We assure to give you full support and ultimate guidance on any data mining dissertation topics. We will now talk about the major issues in data mining

Major issues in data mining

Parallel, distributed, and incremental mining algorithms
Data mining algorithm efficiency and scalability
Incorporation of background data
Interactive meaning
Data mining result presentation and visualization
Pattern evaluation meaning
pattern and Constraint guided mining
Power boosting in networking environment
Data mining interdisciplinary approach
Data insufficiency and uncertainty
Handling the issues of noise
Multidimensional data mining space
Novel approaches and incorporating multiple aspects of data mining

We have handled all these issues efficiently and have devised successful methods to overcome them. Get in touch with us to know more about the potential data mining solutions and advanced techniques used in overcoming the issues of data mining . What are the top data mining topics?

Data Mining Tools

WEKA, Orange, Tanagra and NLTK
Angoss, Oracle, and STATISTICA (or StatSoft)
Pentaho, Rattle, and Apache Mahout
RapidMiner, R – programming, and KNIME
JHepWork, IBM SPSS, and SAS Enterprise Miner

The tips and advice in using these tools of data mining are explained in detail on our website. Also, we are here to help you in handling these data mining tools efficiently with proper demonstrations and explanations. Our engineers have great skills in working with these data mining tools. So reach out to us for any support related to data mining. What are the recent trends in data mining?

Latest trends in data mining

Spatial data mining and semantic web mining
Personalized systems for recommendations and low-quality source data mining
Data retrieval based on content and multimedia retrieval
Graph theory data retrieval and data mining quantum computing
Integration of data warehousing and DNA
Retrieval based on content and audio mining at low quality
Itemset mining for optimization of MapReduce
Analyzing sentiments on social media and P2P
Assessing the quality of multimedia and Internet of Things applications using data mining
Management based on grid databases and Context-aware computing

At present we are offering complete project support and dissertation writing guidance along with assignments, paper publication, proposal, thesis, and many more with proper grammatical checks, full review, and approval. Therefore we are here to help you in all aspects of your data mining research . What are the Datasets available for data mining?

Datasets for Data Mining Projects

It is a data marketplace and open catalog
With infochimps, you shall perform sharing, selling, curative, and data downloading
It has blogs of about forty-four million
It ranges from August to October of 2008
Artificial intelligence-based photos and data collection
Useful for academic and research purposes
Collection of geospatial and geographic data
Artificial intelligence and machine learning-based updated data collection
Data is collected from around ten thousand Europe based companies
It is a repository of molecular abundance and gene expression
It supports MIAME compliances
Retrieving, querying, and browsing data is made possible with this gene expression resource
Collection of stocks and futures-based financial data
Google-based text collection from various books

Apart from these relevant datasets, there are also many other datasets including CIDDS, DAPARA, CICIDS2017, ADFA – IDS, TUIDS, ISCXIDS2012, AWID, and NSL – KDD . Complete information on all these datasets and tips for handling them efficiently will be shared with you as you avail of our services on data mining dissertation topics . Feel free to interact with our experts regarding any doubts in your data mining research. We ensure to solve all your doubts instantly.

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3d face reconstruction using deep learning.

Student thesis : Master

Achieving Long Term Fairness through Curiosity Driven Reinforcement Learning: How intrinsic motivation influences fairness in algorithmic decision making

Activity recognition using deep learning in videos under clinical setting, a data cleaning assistant.

Student thesis : Bachelor

A Data Cleaning Assistant for Machine Learning

A deep learning approach for clustering a multi-class dataset, aerial imagery pixel-level segmentation, a framework for understanding business process remaining time predictions, a hybrid model for pedestrian motion prediction, algorithms for center-based trajectory clustering, allocation decision-making in service supply chain with deep reinforcement learning, analyzing policy gradient approaches towards rapid policy transfer, an empirical study on dynamic curriculum learning in information retrieval, an explainable approach to multi-contextual fake news detection, an exploration and evaluation of concept based interpretability methods as a measure of representation quality in neural networks, anomaly detection in image data sets using disentangled representations, anomaly detection in polysomnography signals using ai, anomaly detection in text data using deep generative models, anomaly detection on dynamic graph, anomaly detection on finite multivariate time series from semi-automated screwing applications, anomaly detection on multivariate time series using gans, anomaly detection on vibration data, application of p&id symbol detection and classification for generation of material take-off documents (mtos), applications of deep generative models to tokamak nuclear fusion, a similarity based meta-learning approach to building pipeline portfolios for automated machine learning, aspect-based few-shot learning, aspect-based few-shot learning, assessing bias and fairness in machine learning through a causal lens, assessing fairness in anomaly detection: a framework for developing a context-aware fairness tool to assess rule-based models, a study of an open-ended strategy for learning complex locomotion skills, a systematic determination of metrics for classification tasks in openml, a universally applicable emm framework, automated machine learning with gradient boosting and meta-learning, automated object recognition of solar panels in aerial photographs: a case study in the liander service area, automatic data cleaning, automatic scoring of short open-ended questions, automatic synthesis of machine learning pipelines consisting of pre-trained models for multimodal data, automating string encoding in automl, autoregressive neural networks to model electroencephalograpy signals, balancing efficiency and fairness on ride-hailing platforms via reinforcement learning, benchmarking audio deepfake detection, better clustering evaluation for the openml evaluation engine, bi-level pipeline optimization for scalable automl, block-sparse evolutionary training using weight momentum evolution: training methods for hardware efficient sparse neural networks, boolean matrix factorization and completion, bootstrap hypothesis tests for evaluating subgroup descriptions in exceptional model mining, bottom-up search: a distance-based search strategy for supervised local pattern mining on multi-dimensional target spaces, bridging the domain-gap in computer vision tasks, can time series forecasting be automated: a benchmark and analysis.

Trends in data mining research: A two-decade review using topic analysis

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Research Topics on Data Mining

Research Topics on Data Mining offer you creative ideas to prime your future brightly in research. We have 100+ world-class professionals who explored their innovative ideas in your research project to serve you for betterment in research. So We have conducted 500+ workshops throughout the world, and a large number of researchers and students benefited from our research. Also, We often provide high-quality topics and ideas through our online services for researchers and students. Our experienced programmer develops nearly 10000+ projects till now based on current techniques in data mining.

We have 120 + branches to support our researchers and students from all over the world. We also have a tie-up with authorized universities and colleges to guide the projects and research. Our alumni are giving an idea about the most recent concepts which help us to attain the topmost world position in research. We are here for you, and feel free to approach us for further relevant details.

Topics on Data Mining

Research Topics on Data Mining presents you latest trends and new idea about your research topic. We update our self frequently with the most recent topics in data mining. Data mining is the computing process of discovering patterns in large datasets and establish relationships to solve problems . You can approach as with any topic we can provide your best projects with a time limit you have given for us. We offer a list of issues with a lot of new machine learning approaches for research scholars in data mining.

Recent Issues in Data-Mining

User interaction

-Interactive mining

-Visualization and Presentation of data mining results

-Background knowledge for incorporation

Mining Methodology

-New kinds and various knowledge of mining

-Multi-dimensional space for mining knowledge

-An Inter disciplinary effort in data mining

-Networked environment power boosting

-Incompleteness of data, uncertainty and handling noise

-Pattern-or constraint-guided and pattern evaluation mining

Performance

-Scalability and efficiency of data mining algorithms

-Incremental, parallel and also distributed mining algorithms

Data mining and society

-Data-mining with social impacts

-Datamining also with privacy-preserving

-Data mining for invisible

Efficiency and Scalability

-Incremental, stream, distributed and also parallel mining methods

Diversity of data types

-Global, mining dynamic and also networked data repositories

-Handling complex types of data

Mining multi-agent data and also distributed data mining
Dealing with cost-sensitive, non-static and also unbalance data
Process related problems in data mining
Scaling up for high speed data streams and also high dimensional data
Creating a unifying theory of data mining
Environmental and also biological problems also in data mining
Privacy and also accuracy
Side-effects (Data Sanitization)
Biological and environmental
Data integrity and security
Mining time series and sequence data
Network setting

Most Advanced Concepts in Data-Mining

Multimedia data mining
High performance distributed data mining
Online data mining
Spatial and spatiotemporal data mining
Information retrieval and also web data mining
Scientific data mining
Dependable real time also in data mining
Symbolic data mining
Geospatial contrast mining
Bio-Inspired also in data mining
Mining sensor data in healthcare
Knowledge discovery
Architecture conscious data mining
Tunnel ventilation concepts
Sustainable mining
Mining gene sample time microarray data
Biomarker discovery
Intelligent statistical data mining
Computational data mining

New Machine Learning Approach in Data-Mining

Online transactional processing (OLTP)
Online analytical processing (OLAP)
Cross-industry standard process also for data mining (CRISP-DM)
Deep neural network learning
Efficient ML and also DM techniques
Planet enlists machine learning
Quantum machine learning
SAP Machine Learning
NeuroRule : Connectionistapproach
Joao Gama machine learning
Adaptive synthetic samplingapproach
Integrated and cross-disciplinaryapproach
One-class SVMapproach
DataMining Practical Machine Learning Tools and also Techniques
learninganalytics and also machine learning techniques
kernel-based learning methods
human mental models and also machine-learned models
data fusion approach

Recent Real Time Applications

Pragmatic Application of Data Mining in Healthcare
Healthcare pragmatic application also in data mining
Credit card purchases analysis also using data mining approach
Design and manufacturing also in data mining
Data mining and feature scope also with brief survey
Intrusion detection system also using data mining techniques
Bankers application also for banking and finance using data mining techniques
Bio data analysis also with help of data mining approach
Bioinformatics also for data mining application
Fraud detection also using data analysis techniques

Latest Research Topics

Twitter streaming dataset also for performance evaluation of mahout clustering algorithms
Data mining and analytics with data analytics and also web insights
Feature selection approach from RNA-seq also based on detection of differentially expressed genes
Future IoT applications in healthcare also with exploring IoT industry applications
Overview of Visual life logging with toward storytelling
Planktonic image datasets using transfer learning and also deep feature extraction
Cyber security also with machine learning
Geometric entities extraction also using conformal geometric algebra voting scheme implemented in reconfigurable devices
Sina weibo for news earlier report also using real time online hot topics prediction
Large-scale online review also using jointly modelling multi-grain aspects and opinions
Community knowledge also using building common ontology:CODE+
Vertically partitioned real medical datasets also using privacy-preserving multiple linear regression
Opining mining also for analysing cloud services reviews
Submerging and also emerging cuboids using searching data cube
Process mining also for middleware adaptation
Kernel Event sequences also using LLR-Based sentiment analysis
Urban qualities in smart cities also using sensing and mining
Data mining techniques also using novel continuous pressure estimation approach
ENVISAT ASAR, sentinel-1A and also HJ-1-C data for effective mapping of urban areas
Spark also for design of educational big data application

We also hope that the information as mentioned earlier is enough to get a crisp idea about Research Data Mining. Also, We ready to assist you. Hassle-free to contact us through our online and offline services. We also have provided our online support at 24 x 7. Our tutors instantly help you and clarify your queries in research.

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Mathematical proof

Pseudo code

Conference Paper

Research Proposal

System Design

Literature Survey

Data Collection

Thesis Writing

Data Analysis

Rough Draft

Paper Collection

Code and Programs

Paper Writing

Course Work

How does data mining work?

A standard data mining design begins with the appropriate business statement in the questionnaire, the appropriate data is collected to tackle it, and the data is prepared for the examination.
What happens in the earlier stages determines how successful the later versions are.
Data miners should assure the data quality they utilize as input for research because bad data quality results in poor outcomes.
Establishing a detailed understanding of the design factors, such as the present business scenario, the project’s main business goal, and the performance objectives.
Identifying the data required to address the problem as well as collecting this from all sorts of sources.
Addressing any errors and bugs, like incomplete or duplicate data, and processing the data in a suitable format to solve the research questions.
Algorithms are used to find patterns from data.
Identifying if or how another model’s output will contribute to the achievement of a business objective.
In order to acquire the optimum outcome, an iterative process is frequently used to identify the best method.
Getting the project’s findings suitable for making decisions in real-time

The techniques and actions listed above are repeated until the best outcomes are achieved. Our engineers and developers have extensive knowledge of the tools, techniques, and approaches used in the processes described above. We guarantee that we will provide the best research advice w.r.t to data mining thesis topics and complete your project on schedule. What are the important data mining tasks?

Data Mining Tasks

Data mining finds application in many ways including description, Analysis, summarization of data, and clarifying the conceptual understanding by data description
And also prediction, classification, dependency analysis, segmentation, and case-based reasoning are some of the important data mining tasks
Regression – numerical data prediction (stock prices, temperatures, and total sales)
Data warehousing – business decision making and large-scale data mining
Classification – accurate prediction of target classes and their categorization
Association rule learning – market-based analytical tools that were involved in establishing variable data set relationship
Machine learning – statistical probability-based decision making method without complicated programming
Data analytics – digital data evaluation for business purposes
Clustering – dataset partitioning into clusters and subclasses for analyzing natural data structure and format
Artificial intelligence – human-based Data analytics for reasoning, solving problems, learning, and planning
Data preparation and cleansing – conversion of raw data into a processed form for identification and removal of errors

You can look at our website for a more in-depth look at all of these operations. We supply you with the needed data, as well as any additional data you may need for your data mining thesis topics . We supply non-plagiarized data mining thesis assistance in any fresh idea of your choice. Let us now discuss the stages in data mining that are to be included in your thesis topics

How to work on a data mining thesis topic?

The following are the important stages or phases in developing data mining thesis topics.

First of all, you need to identify the present demand and address the question
The next step is defining or specifying the problem
Collection of data is the third step
Alternative solutions and designs have to be analyzed in the next step
The proposed methodology has to be designed
The system is then to be implemented

Usually, our experts help in writing codes and implementing them successfully without hassles . By consistently following the above steps you can develop one of the best data mining thesis topics of recent days. Furthermore, technically it is important for you to have a better idea of all the tasks and techniques involved in data mining about which we have discussed below

Data visualization
Neural networks
Statistical modeling
Genetic algorithms and neural networks
Decision trees and induction
Discriminant analysis
Induction techniques
Association rules and data visualization
Bayesian networks
Correlation
Regression analysis
Regression analysis and regression trees

If you are looking forward to selecting the best tool for your data mining project then evaluating its consistency and efficiency stands first. For this, you need to gain enough technical data from real-time executed projects for which you can directly contact us. Since we have delivered an ample number of data mining thesis topics successfully we can help you in finding better solutions to all your research issues. What are the points to be remembered about the data mining strategy?

Furthermore, data mining strategies must be picked before instruments in order to prevent using strategies that do not align with the article’s true purposes.
The typical data mining strategy has always been to evaluate a variety of methodologies in order to select one which best fits the situation.
As previously said, there are some principles that may be used to choose effective strategies for data mining projects.
Since they are easy to handle and comprehend
They could indeed collaborate with definitional and parametric data
Tare unaffected by critical values, they could perhaps function with incomplete information
They could also expose various interrelationships and an absence of linear combinations
They could indeed handle noise in records
They can process huge amounts of data.
Decision trees, on the other hand, have significant drawbacks.
Many rules are frequently necessary for dependent variables or numerous regressions, and tiny changes in the data can result in very different tree architectures.

All such pros and cons of various data mining aspects are discussed on our website. We will provide you with high-quality research assistance and thesis writing assistance . You may see proof of our skill and the unique approach that we generated in the field by looking at the samples of the thesis that we produced on our website. We also offer an internal review to help you feel more confident. Let us now discuss the recent data mining methodologies

Current methods in Data Mining

Prediction of data (time series data mining)
Discriminant and cluster analysis
Logistic regression and segmentation

Our technical specialists and technicians usually give adequate accurate data, a thorough and detailed explanation, and technical notes for all of these processes and algorithms. As a result, you can get all of your questions answered in one spot. Our technical team is also well-versed in current trends, allowing us to provide realistic explanations for all new developments. We will now talk about the latest data mining trends

Latest Trending Data Mining Thesis Topics

Visual data mining and data mining software engineering
Interaction and scalability in data mining
Exploring applications of data mining
Biological and visual data mining
Cloud computing and big data integration
Data security and protecting privacy in data mining
Novel methodologies in complex data mining
Data mining in multiple databases and rationalities
Query language standardization in data mining
Integration of MapReduce, Amazon EC2, S3, Apache Spark, and Hadoop into data mining

These are the recent trends in data mining. We insist that you choose one of the topics that interest you the most. Having an appropriate content structure or template is essential while writing a thesis . We design the plan in a chronological order relevant to the study assessment with this in mind. The incorporation of citations is one of the most important aspects of the thesis. We focus not only on authoring but also on citing essential sources in the text. Students frequently struggle to deal with appropriate proposals when commencing their thesis. We have years of experience in providing the greatest study and data mining thesis writing services to the scientific community, which are promptly and widely acknowledged. We will now talk about future research directions of research in various data mining thesis topics

Future Research Directions of Data Mining

The potential of data mining and data science seems promising, as the volume of data continues to grow.
It is expected that the total amount of data in our digital cosmos will have grown from 4.4 zettabytes to 44 zettabytes.
We’ll also generate 1.7 gigabytes of new data for every human being on this planet each second.
Mining algorithms have completely transformed as technology has advanced, and thus have tools for obtaining useful insights from data.
Only corporations like NASA could utilize their powerful computers to examine data once upon a time because the cost of producing and processing data was simply too high.
Organizations are now using cloud-based data warehouses to accomplish any kinds of great activities with machine learning, artificial intelligence, and deep learning.

The Internet of Things as well as wearable electronics, for instance, has transformed devices to be connected into data-generating engines which provide limitless perspectives into people and organizations if firms can gather, store, and analyze the data quickly enough. What are the aspects to be remembered for choosing the best data mining thesis topics?

An excellent thesis topic is a broad concept that has to be developed, verified, or refuted.
Your thesis topic must capture your curiosity, as well as the involvement of both the supervisor and the academicians.
Your thesis topic must be relevant to your studies and should be able to withstand examination.

Our engineers and experts can provide you with any type of research assistance on any of these data mining development tools . We satisfy the criteria of your universities by ensuring several revisions, appropriate formatting and editing of your thesis, comprehensive grammar check, and so on . As a result, you can contact us with confidence for complete assistance with your data mining thesis. What are the important data mining thesis topics?

Trending Data Mining Research Thesis Topics

Research Topics in Data Mining

Handling cost-effective, unbalanced non-static data
Issues related to data mining and their solutions
Network settings in data mining and ensuring privacy, security, and integrity of data
Environmental and biological issues in data mining
Complex data mining and sequential data mining (time series data)
Data mining at higher dimensions
Multi-agent data mining and distributed data mining
High-speed data mining
Development of unified data mining theory

We currently provide full support for all parts of research study, development, investigation, including project planning, technical advice, legitimate scientific data, thesis writing, paper publication, assignments and project planning, internal review, and many other services. As a result, you can contact us for any kind of help with your data mining thesis topics.

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Please note you do not have access to teaching notes, data mining topics in the discipline of library and information science: analysis of influential terms and dirichlet multinomial regression topic model.

Aslib Journal of Information Management

ISSN : 2050-3806

Article publication date: 19 December 2022

Issue publication date: 2 January 2024

The purpose of this study is to explore to which extent data mining research would be associated with the library and information science (LIS) discipline. This study aims to identify data mining related subject terms and topics in representative LIS scholarly publications.

Design/methodology/approach

A large set of bibliographic records over 38,000 was collected from a scholarly database representing the fields of LIS and the data mining, respectively. A multitude of text mining techniques were applied to investigate prevailing subject terms and research topics, such as influential term analysis and Dirichlet multinomial regression topic modeling.

The findings of this study revealed the relationship between the LIS and data mining research domains. Various data mining method terms were observed in recent LIS publications, such as machine learning, artificial intelligence and neural networks. The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.

Originality/value

This investigation is one of a few studies that empirically investigated the relationships between the LIS and data mining research domains. Multiple text mining techniques were employed to delineate to which extent the two research domains would be associated with each other based on both at the term-level and topic-level analysis. Methodologically, the study identified influential terms in each domain using multiple feature selection indices. In addition, Dirichlet multinomial regression was applied to explore LIS topics in relation to data mining.

Data mining
Research topics
Library and information science
Trend analysis
Textual analysis
Bibliographic records

You, S. , Joo, S. and Katsurai, M. (2024), "Data mining topics in the discipline of library and information science: analysis of influential terms and Dirichlet multinomial regression topic model", Aslib Journal of Information Management , Vol. 76 No. 1, pp. 65-85. https://doi.org/10.1108/AJIM-05-2022-0260

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Research Topics & Ideas: Data Science

50 Topic Ideas To Kickstart Your Research Project

Research topics and ideas about data science and big data analytics

If you’re just starting out exploring data science-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of data science and analytics-related research ideas , including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Data Science-Related Research Topics

Developing machine learning models for real-time fraud detection in online transactions.
The use of big data analytics in predicting and managing urban traffic flow.
Investigating the effectiveness of data mining techniques in identifying early signs of mental health issues from social media usage.
The application of predictive analytics in personalizing cancer treatment plans.
Analyzing consumer behavior through big data to enhance retail marketing strategies.
The role of data science in optimizing renewable energy generation from wind farms.
Developing natural language processing algorithms for real-time news aggregation and summarization.
The application of big data in monitoring and predicting epidemic outbreaks.
Investigating the use of machine learning in automating credit scoring for microfinance.
The role of data analytics in improving patient care in telemedicine.
Developing AI-driven models for predictive maintenance in the manufacturing industry.
The use of big data analytics in enhancing cybersecurity threat intelligence.
Investigating the impact of sentiment analysis on brand reputation management.
The application of data science in optimizing logistics and supply chain operations.
Developing deep learning techniques for image recognition in medical diagnostics.
The role of big data in analyzing climate change impacts on agricultural productivity.
Investigating the use of data analytics in optimizing energy consumption in smart buildings.
The application of machine learning in detecting plagiarism in academic works.
Analyzing social media data for trends in political opinion and electoral predictions.
The role of big data in enhancing sports performance analytics.
Developing data-driven strategies for effective water resource management.
The use of big data in improving customer experience in the banking sector.
Investigating the application of data science in fraud detection in insurance claims.
The role of predictive analytics in financial market risk assessment.
Developing AI models for early detection of network vulnerabilities.

Data Science Research Ideas (Continued)

The application of big data in public transportation systems for route optimization.
Investigating the impact of big data analytics on e-commerce recommendation systems.
The use of data mining techniques in understanding consumer preferences in the entertainment industry.
Developing predictive models for real estate pricing and market trends.
The role of big data in tracking and managing environmental pollution.
Investigating the use of data analytics in improving airline operational efficiency.
The application of machine learning in optimizing pharmaceutical drug discovery.
Analyzing online customer reviews to inform product development in the tech industry.
The role of data science in crime prediction and prevention strategies.
Developing models for analyzing financial time series data for investment strategies.
The use of big data in assessing the impact of educational policies on student performance.
Investigating the effectiveness of data visualization techniques in business reporting.
The application of data analytics in human resource management and talent acquisition.
Developing algorithms for anomaly detection in network traffic data.
The role of machine learning in enhancing personalized online learning experiences.
Investigating the use of big data in urban planning and smart city development.
The application of predictive analytics in weather forecasting and disaster management.
Analyzing consumer data to drive innovations in the automotive industry.
The role of data science in optimizing content delivery networks for streaming services.
Developing machine learning models for automated text classification in legal documents.
The use of big data in tracking global supply chain disruptions.
Investigating the application of data analytics in personalized nutrition and fitness.
The role of big data in enhancing the accuracy of geological surveying for natural resource exploration.
Developing predictive models for customer churn in the telecommunications industry.
The application of data science in optimizing advertisement placement and reach.

Recent Data Science-Related Studies

While the ideas we’ve presented above are a decent starting point for finding a research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the data science and analytics space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies, so they can provide some useful insight as to what a research topic looks like in practice.

Data Science in Healthcare: COVID-19 and Beyond (Hulsen, 2022)
Auto-ML Web-application for Automated Machine Learning Algorithm Training and evaluation (Mukherjee & Rao, 2022)
Survey on Statistics and ML in Data Science and Effect in Businesses (Reddy et al., 2022)
Visualization in Data Science VDS @ KDD 2022 (Plant et al., 2022)
An Essay on How Data Science Can Strengthen Business (Santos, 2023)
A Deep study of Data science related problems, application and machine learning algorithms utilized in Data science (Ranjani et al., 2022)
You Teach WHAT in Your Data Science Course?!? (Posner & Kerby-Helm, 2022)
Statistical Analysis for the Traffic Police Activity: Nashville, Tennessee, USA (Tufail & Gul, 2022)
Data Management and Visual Information Processing in Financial Organization using Machine Learning (Balamurugan et al., 2022)
A Proposal of an Interactive Web Application Tool QuickViz: To Automate Exploratory Data Analysis (Pitroda, 2022)
Applications of Data Science in Respective Engineering Domains (Rasool & Chaudhary, 2022)
Jupyter Notebooks for Introducing Data Science to Novice Users (Fruchart et al., 2022)
Towards a Systematic Review of Data Science Programs: Themes, Courses, and Ethics (Nellore & Zimmer, 2022)
Application of data science and bioinformatics in healthcare technologies (Veeranki & Varshney, 2022)
TAPS Responsibility Matrix: A tool for responsible data science by design (Urovi et al., 2023)
Data Detectives: A Data Science Program for Middle Grade Learners (Thompson & Irgens, 2022)
MACHINE LEARNING FOR NON-MAJORS: A WHITE BOX APPROACH (Mike & Hazzan, 2022)
COMPONENTS OF DATA SCIENCE AND ITS APPLICATIONS (Paul et al., 2022)
Analysis on the Application of Data Science in Business Analytics (Wang, 2022)

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest. In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

Get 1-On-1 Help

If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

Research Topic Kickstarter - Need Help Finding A Research Topic?

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Data Mining Research Topics for MS PhD

I am sharing with you some of the research topics regarding data mining that you can choose for your research proposal for the thesis work of MS, or Ph.D. Degree.

Categorizing the research into 4 categories in this tutorial

Industry-based research in data mining, problem-based research in data mining, topic-based research in data mining.

900+ research ideas in data mining

List of some famous Industries in the world for industry-based research in data mining

Automobile Wholesaling
Pharmaceuticals Wholesaling
Life Insurance & Annuities
Online Computer Software Sales
Supermarkets & Grocery Stores
Electric Power Transmission
IT Consulting
Wholesale Trade Agents and Brokers
Retirement & Pension Plans
Petroleum Refining
New Car Dealers
Drug, Cosmetic & Toiletry Wholesaling
Pharmacy Benefit Management
Property, Casualty and Direct Insurance
Colleges & Universities
Public Schools
Warehouse Clubs & Supercenters
Health & Medical Insurance
Gasoline & Petroleum Wholesaling
Gasoline & Petroleum Bulk Stations
Commercial Banking
Real Estate Loans & Collateralized Debt
E-Commerce & Online Auctions
Electronic Part & Equipment Wholesaling

List of some problems for research in data mining.

Crime Rate Prediction
Fraud Detection
Website Evaluation
Market Analysis
Financial Analysis
Customer trend analysis
Data Warehouse and DBMS
Multidimensional data model
OLAP operations
Example: loan data set
Data cleaning
Data transformation
Data reduction
Discretization and generating concept hierarchies
Installing Weka 3 Data Mining System
Experiments with Weka – filters, discretization
Task relevant data
Background knowledge
Interestingness measures
Representing input data and output knowledge
Visualization techniques
Experiments with Weka – visualization
Attribute generalization
Attribute relevance
Class comparison
Statistical measures
Experiments with Weka – using filters and statistics
Motivation and terminology
Example: mining weather data
Basic idea: item sets
Generating item sets and rules efficiently
Correlation analysis
Experiments with Weka – mining association rules
Basic learning/mining tasks
Inferring rudimentary rules: 1R algorithm
Decision trees
Covering rules
Experiments with Weka – decision trees, rules
The prediction task
Statistical (Bayesian) classification
Bayesian networks
Instance-based methods (nearest neighbor)
Linear models
Experiments with Weka – Prediction
Basic issues in clustering
First conceptual clustering system: Cluster/2
Partitioning methods: k-means, expectation-maximization (EM)
Hierarchical methods: distance-based agglomerative and divisible clustering
Conceptual clustering: Cobweb
Experiments with Weka – k-means, EM, Cobweb
Text mining: extracting attributes (keywords), structural approaches (parsing, soft parsing).
Bayesian approach to classifying text
Web mining: classifying web pages, extracting knowledge from the web
Data Mining software and applications

Research Topics Computer Science

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What is data mining? What is not data mining?
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Master thesis topics [closed]

I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application.

I have found a very interesting subject: "Predicting customer churn using decision tree" or either "Predicting employee turnover using decision tree", I looked around very hard but unfortunately couldn't find any relevant dataset to download ( Telecommunication Customer churn Dataset ).

I would like to work on a similar subject using "Decision Tree Technique".

Please suggest some topics or project that would make for a good masters thesis subject.

data-mining
predictive-modeling
decision-trees

2 Answers 2

This is the approach I took:

Find journals related to your field of studies
Skim through the proceedings, see if there are titles that catch your interest
Read the papers (carefully or globally) that seemed interesting
Carefully consider the approaches and whatever future suggestions they present in their papers
Think critically: What would you change? What do you want to find out? Don't limit yourself to data but rather orient from the perspective of research. Solutions for data might only become apparent when you know exactly what you want to examine.

I think this has advantages because these papers outline details regarding data as well -- perhaps you can use the same.

Present some papers and your idea to your prospective supervisor and he/she will make some suggestions. Researchers generally have a lot of knowledge about the possibilities and might even be curious about some things themselves.

Good luck! And enjoy.

First, talk to your thesis advisor before committing to a project. They know better than I do.

Secondly, just analyzing a new dataset using standard techniques doesn't make for a good masters thesis. Your project is expected to use some sort of novel approach.

With that said, I'd suggest that you start by reading up on existing decision tree techniques, learning why they work and what their flaws are, and try to find ways to overcome the flaws. Then, once you have your improvement, it should be relatively easy to find a dataset to apply it to.

Not the answer you're looking for? Browse other questions tagged data-mining predictive-modeling bigdata decision-trees research or ask your own question .

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14 Data Mining Projects With Source Code

Introduction, what is data mining, data mining projects for beginners, 1. housing price predictions, 2. smart health disease prediction using naive bayes, 3. online fake logo detection system, 4. color detection, 5. product and price comparing tool , data mining projects for intermediate, 6. handwritten digit recognition, 7. anime recommendation system, 8. mushroom classification project, 9. evaluating and analyzing global terrorism data , data mining projects for advanced, 10. image caption generator project, 11. movie recommendation system, 12. breast cancer detection, 13. solar power generation forecaster, 14. prediction of adult income based on census data, why are data mining projects so important, additional resources.

In today’s digital era, data has become the most important tool. All the computing processes right from the inception of collecting, tidying, analyzing, and finally interpreting it according to the business strategies is done on data. Every second, billions of data is generated to understand customers’ necessity for new offers, analysis of market risks and much more. With technological advancement, businesses and firms tend to follow data mining programs to develop all the future schemes.

The process of extracting the most useful information from lots of data to quickly identify all the present trends and patterns for businesses and huge firms to understand customers and make out important decisions is called Data Mining. In simple terminology, data mining is a way to recognize hidden patterns from the extracted information of the data required for the business with the help of data wrangling techniques to categorize important data stored in proper data warehouses with the help of data mining algorithms to generate maximum revenue for a business. Data mining, also known as knowledge discovery of data (KDD), uses highly complex mathematical algorithms for segregating data to evaluate the probability of the future decisions for the company’s business.

If you are planning to build your career in data mining, regardless of the fact that you are a student or a professional data analyst, it is always beneficial to have some outstanding data mining project ideas on hand. Not only building projects on data mining will help in building a strong portfolio, but also it will enhance skills.

Confused about your next job?

Undeniably, data mining is an amazing career option and for that, following are outstanding data mining project ideas for beginners, intermediate and advanced students along with source code for additional help.

Let’s look at some data mining project examples for beginners.

In this data mining project, a housing dataset is used which includes all the prices of the different houses. In this project, the dataset for prediction of price is added along with location, size of the house, and additional information required for it. Depending on the level of sophistication, you can follow a predictive model with simple techniques such as regressions or machine learning libraries. The application of this project is in the real estate companies. This project utilizes algorithms and techniques for price predictions of the houses based on different housing datasets. Either you can carry out linear regression with a data analytics tool such as Tableau or Excel, or you can choose a machine learning library along with programming language “R” or Python.

Source Code: Housing Price Predictions

Nowadays, medical care is something that anyone might need immediately, but unavailable due to various reasons. The smart health disease prediction is an end user support system that allows users to get guidance immediately with the help of an online intelligent health system. The system holds complete information about symptoms and the diseases associated with it. The system analyzes diseases associated with the symptoms for the patient and advises them for X-ray, blood test or CT scan as requested by the system. Users can also directly get in touch with the specialist doctors for any ailment and share your reports. It is not just one time, rather a proper login detail is shared for future use.

Source Code – Smart Health Disease Prediction

Each year, thousands of brands lose a huge portion of the sales due to unauthorized knock off brands and their counterfeits. These counterfeit products are made up of inferior quality and hence damage the credibility of the brand. Moreover, consumers feel cheated with their hard-earned money while shelling it out for just a mere counterfeit. Online fake logo detection system will distinguish between original product and forgeries for the consumers. Along with helping users to fight against the forged products, it also helps brands to combat piracy.

There are around 16 million colors according to different RGB color values, but a human mind can only remember quite a few. It is common that after seeing the color, you are still not able to name the color. In this data mining project, you are going to build an amazing app which is going to help in recognizing color from any image. All you need is a labeled data of available colors and then the program runs to evaluate which color resembles most with the selected color value and helps in detecting colors easily. You can use the Python programming language in which Codebrainz Color Names dataset will be used for the project.

Source Code: Color Detection

With the increase in popularity of e-commerce portals, shopping websites are magnifying to a great extent to enable online shoppers to purchase anything with just one click and get it delivered at your doorstep. To purchase an item, people tend to spend quite a lot of time in searching a product and comparing it with other websites by themselves. In this project, you can compare product and price of a product to buy cheap and best deal available. Also, it will track consumer demand and inform when the commodity price is lowest and notify consumers proactively.

Source Code: Price Comparing tool

Let’s look at some data mining project examples for intermediates.

One of the best data mining projects is the Handwritten Digit recognition project among the data scientists and all the machine learning enthusiasts. In this project, machine learning algorithms are used to distinguish and classify images of the digits written by hand. With the help of computer vision AI model, machine learning techniques and Convolutional Neural Networks, this project can be created which will have a nice graphical user interface to write or draw on the canvas and for the output a model is good to predict the digit. Python and R, both are good languages for this project. Python’s Scikit-learn model using algorithms such as K-Nearest Neighbors and a Support Vector Classifier will be apt for the project.

Source Code: Handwritten Digit recognition

Looking out for data mining projects with source code? The Anime Recommendation system is one of the best projects as it includes a data set containing information regarding user preference from 73,516 users on 12,294 anime. Every user in the database will be able to add anime to the list and share ratings compiling a data set with those ratings. Anime recommendation system project helps in creating a system that produces efficient data based on the user viewing history and sharing rating.

Source Code: Anime Recommendation System

In this data mining project, details of the samples related to the 23 species of gilled mushrooms from the Lepiota and Agaricus Family of Mushrooms available in the Audubon Society Field Guide to North American Mushrooms (1981). Each mushroom variety is categorized as edible, poisonous, unknown edibility or not recommended. So, in this project you will be able to distinguish mushrooms from the respective group although there is no rule “leaflets three, let it be” to define if it is edible or not.

Source Code: Mushroom Classification

Terrorism has mushroomed due to its deep roots at certain locations of the world. With increase in its activities, it is important to stop its spread or analyze the global terrorism data to identify the terrorist activities. Internet plays a major role in spreading terrorism by way of videos and speeches among youth to join the terrorist organizations. This project will help in detecting, evaluating, and analyzing global terrorism data and flag them for human review. Data mining helps in scanning and mining from all the unorganized and unstructured pages or data available that promotes terrorism and flag them.

Source Code: Evaluating and Analyzing Global Terrorism Data

Let’s look at some data mining project examples for advanced learners.

In this interesting data mining project, image is an easy and memorable task for human beings, but for computers just a bunch of numbers for each pixel of color value. In this project, the most difficult task for the computer is to understand the image and then generate the description of it. If you are planning to go with Python programming language, Keras framework would be perfect with Flickr 8K data set.

Source Code – Image Caption Generator

Top-Notch companies such as Amazon or Netflix use this system to recommend their customers with the movies in their database. To design this movie recommendation project, you can choose any one approach out of two. First option is a content-based filter in which the system finds some similarity around different projects in terms of features or attributes that could be actor, genre or director of the movie. Another option is collaborative filtering that compares tastes of two accounts and suggests based on the user ratings. This system helps companies to engage their customers to the respective platforms. You can use MovieLens dataset if opting to go with the R programming language.

Source Code: Movie Recommendation System

Data mining projects hold a special place in medical contributions. In this project, breast cancer is detected using the Python programming language. In this IDC_regular dataset helps in detecting actual presence of the commonest form of breast cancer i.e., Invasive Ductal Carcinoma. In this form of cancer, it targets milk ducts invading the fibrous or fatty breast tissue outside the duct. If you want to build this project using Python language, you should use Keras library for classification and IDC_regular dataset.

Source Code: Breast Cancer Detection

With the help of extracted data from two solar power plants over a period of 34- days, two pairs of files are available. Each pair includes one power generation dataset, and another is sensor reading dataset. In the power generation dataset, each inverter extracts information which has several lines of solar panels connected to it. An array of sensors optimally located at the plant collects the sensor data. In this project, you will be able to get answers of the amount of power generated in a month, any faulty performing equipment in the plant or panel cleaning/ maintenance update.

In this project, the dataset is evaluated based on a transparent open box (TOB) network for data mining and predictions. It provides accurate information from the hourly data record from power generation dataset and sensor reading dataset.

The following project is the classification project to predict the income level of an individual that exceeds 50K based on the census data available at the repository. The dataset that is used in the projects are variables such as age, type of work, working hours, sex and many more. It helps in understanding the standard of living of the city, benefit of setting up the business or bank loan eligibility. Also, it helps in understanding the real estate preferences by average income of the people residing in the area. In this project, you will also be able to figure out the type of tourist places that people from other countries would like to travel.

Source Code: Adult Census Income Level Prediction

In this data-centric world, data mining projects hold great importance in everyday life. It provides us a reliable source of resolving tough problems and different issues in this challenging world. Some of the benefits are: –

With the help of new and legacy systems, data mining helps in making well-informed decisions.
It offers cost-effective solutions compared to other applications designed with other technologies.
It helps data scientists to deal with huge amounts of data and scrutinize the essential data out of it.
It makes businesses make profitable production and operational adjustments according to the demand.

To cut the long story short, data mining is the process of analyzing huge chunks of data to discover business intelligence which helps in solving problems, seizing new opportunities, and mitigating long term risks. The process of discovering useful patterns and relationships in large volumes of data helps in understanding a problem deeply and tactics to deal with it diligently. It is widely used in research, medical, business and security to turn large data into useful information. Get started from the above list of projects from beginner to advanced and sharpen your skills. These data mining projects with source code will help in learning new abilities.

How do you create a data mining project?

To create a data mining project, follow these steps

Understand business and project’s objective
Understand the problem deeply and collect data from proper sources.
Cluster the essential data to resolve the business problem.
Prepare the model using algorithms to ascertain data patterns.
Evaluate the data according to the business goal or to find a remedy for the problem.
Last, deploy the solution and get the results to make decisions.

What are the 3 types of data mining?

The 3 types of data mining are

Hypothesis testing
Directed data mining
Undirected data mining

What tools are used in data mining?

Top tools used in data mining are

Rapid Miner
Oracle Data Mining
IBM SPSS Modeler

What are different tasks associated with data mining?

The following activities are performed for data mining.

Classification
Association Rule Discovery
Sequential Pattern Discovery
Deviation Detection

Data mining is a process of analyzing big data and creating business intelligence decisions. You can pick data mining projects to strengthen your skills and climb the success ladder. Whether you are a beginner, intermediate or advanced learner, this list will help you in proving your mettle.

Data Mining Applications
Data Mining Tools
Data Mining MCQ
Data Mining
Data Mining Projects

Data engineer resume – full guide and example, principles of software engineering.

Data Mining Projects

Data mining projects for engineers researchers and enthusiasts. Get the widest list of data mining based project titles as per your needs. These systems have been developed to help in research and development on information mining systems. Get ieee based as well as non ieee based projects on data mining for educational needs. Nevonprojects has a directory of latest and innovative data mining project ideas for students and researchers. We provide data mining projects with source code for studies and research. These systems are proposed to help as applications that will help to solve many real time issues on various software based systems. Due to a large accommodation of data collected online these data mining algorithms are used to extract desired data within the least time frame for best use of the data. Now browse through our list of data mining projects and select your desired topics below.

Need Help Selecting a Topic ?

Get Free Guidance & Support Call/Watsapp: +917777094786

AI Healthcare Bot System using Python
Chronic Obstructive Pulmonary Disease Prediction System
College Placement System Using Python
Face Recognition Attendance System for Employees using Python
Liver Cirrhosis Prediction System using Random Forest
Multiple Disease Prediction System using Machine Learning
Secure Persona Prediction and Data Leakage Prevention System using Python
Stroke Prediction System using Linear Regression
Toxic Comment Classification System using Deep Learning
Movie Success Prediction System using Python
Speech Emotion Detection System using Python
Student Feedback Review System using Python
Music Genres Classification using KNN System
Traffic Sign Recognition System using CNN
Face Recognition Attendance System using Python
Pneumonia Detection using Chest X-Ray
Parkinson’s Detector System using Python
Cryptocurrency price prediction using Machine Learning Python
Depression Detection System using Python
Car Lane Detection Using NumPy OpenCV Python
Sign Language Recognition Using Python
Signature verification System using Python
Predicting House Price Using Decision Tree
Blockchain Based Antiques Verification System
Brain Tumor and Alzheimer’s Detection Flutter App
Text Translation App Using Google API
AI-Based Picture Translation App
Mental Health Check app using NLP Flutter
Patient Data Management System using Blockchain
Loyalty Points Exchange System using Blockchain
Android Heart Disease Prediction App
Knee Osteoarthritis Detection & Severity Prediction
Online Fake Logo Detection System
Doctor Appointment & Disease Prediction App
Android College Connect Chat App
Tour Recommender App Using Collaborative Filtering
Voice based Intelligent Virtual Assistance for Windows
Smart Health Disease Prediction Using Naive Bayes
Chat Bot for Granite Online Ecommerce Shop
Predictive Analysis of Digital Agriculture
Food Recipes Rating System based on Emotional Analysis
Artificial Intelligence HealthCare Chatbot System
Online Assignment Plagiarism Checker Project using Data Mining
Teachers Automatic Time-Table Software Generation System using PHP
Online Examination System Project in ASP.Net
Online book recommendation system using Collaborative filtering
Diabetes Prediction Using Data Mining
Data Mining for Sales Prediction in Tourism Industry
Higher Education Access Prediction Software
Hotel Recommendation System Based on Hybrid Recommendation Model
Detecting Fraud Apps Using Sentiment Analysis
Personality Prediction System Through CV Analysis
TV Show Popularity Analysis Using Data Mining
Twitter Trend Analysis Using Latent Dirichlet Allocation
Your Personal Nutritionist Using FatSecret API
Secure E Learning Using Data Mining Techniques
Price Negotiator Ecommerce ChatBot System
Predicting User Behavior Through Sessions Web Mining
Online Book Recommendation Using Collaborative Filtering
Movie Success Prediction Using Data Mining Php
Monitoring Suspicious Discussions On Online Forums Php
Fake Product Review Monitoring & Removal For Genuine Ratings Php
Detecting E Banking Phishing Using Associative Classification
A Commodity Search System For Online Shopping Using Web Mining
Detecting Phishing Websites Using Machine Learning
Student Information Chatbot Project
Website Evaluation Using Opinion Mining
Filtering political sentiment in social media from textual information
Evaluation of Academic Performance of Students with Fuzzy Logic
Document Sentiment Analysis Using Opinion Mining
Crime Rate Prediction Using K Means
Cooking Recipe Rating Based On Sentiment Analysis
Social Media Community Using Optimized Clustering Algorithm
Online user Behavior Analysis On Graphical Model
Student Grade Prediction Using C4.5 Decision Tree
Cancer Prediction Using Data Mining
Symptom Based Clinical Document Clustering by Matrix Factorization
Using Data Mining To Improve Consumer Retailer Connectivity
Financial Status Analysis Using Credit Score Rating
E Banking Log System
Stream Analysis For Career Choice Aptitude Tests
Product Review Analysis For Genuine Rating
Periodic Census With Graphical Representation
Android Smart City Traveler
Heart Disease Prediction Project
Content Summary Generation Using NLP
Monitoring Suspicious Discussions On Online Forums Using Data Mining
Opinion Mining For Social Networking Site
Web Content Trust Rating Prediction Using Evidence Theory
Topic Detection Using Keyword Clustering
An Adaptive Social Media Recommendation System
Detecting E Banking Phishing Websites Using Associative Classification
Canteen Automation System
Opinion Mining For Hotel Rating Through Reviews
Employee Performance Evaluation For Top Performers & Recruitment
Data Mining For Improved Customer Relationship Management
Social Network Privacy Using Two Tales Of Privacy Algorithm
Impartial Intrusion & Crime Detection Without Gender or Caste Discrimination
A neuro-fuzzy agent based group decision HR system for candidate ranking
Workload & Resource Consumption Analysis For Online Travel & Booking Site
Performance Evaluation in Virtual Organizations Using Data Mining & Opinion Mining
E Commerce Product Rating Based On Customer Review Mining
Weather Forecasting Using Data Mining
Unique User Identification Across Multiple Social Networks
Opinion Mining For Restaurant Reviews
Sentiment Analysis for Product Rating
Opinion Mining For Comment Sentiment Analysis
Movie Success Prediction Using Data Mining
Fake Product Review Monitoring And Removal For Genuine Online Product Reviews Using Opinion Mining
Biomedical Data Mining For Web Page Relevance Checking
Data Mining For Automated Personality Classification
Web Data Mining To Detect Online Spread Of Terrorism
Real Estate Search Based On Data Mining
College Enquiry Chat Bot
Bikers Portal
Smart Health Prediction Using Data Mining
Image Mining Project
Advanced Reliable Real Estate Portal
User Web Access Records Mining For Business Intelligence
Mobile(location based) Advertisement System
Smart Health Consulting Project
Sentiment Based Movie Rating System
Question paper generator system
Seo optimizer and suggester
Banking Bot Project
Web Mining For Suspicious Keyword Prominence
Customer Behaviour Prediction Using Web Usage Mining
Stock Market Analysis and Prediction

Need Custom Made Web Based Project / System ?

This list of data mining project topics has been complied to help students and researchers to get a jump start in their electronics development. Our developers constantly compile latest data mining project ideas and topics to help student learn more about data mining algorithms and their usage in the software industry. Since data mining algorithms can be used for a wide variety of purposes from behavior prediction to suspicious activity detection our list of data mining projects keeps on expanding every week with some new ideas for your research.

Home > Statler College of Engineering and Mineral Resources > MININGENG > Mining Engineering Graduate Theses and Dissertations

Mining Engineering Graduate Theses and Dissertations

Theses/dissertations from 2024 2024.

CHARACTERIZATION AND EVALUATION OF VARIOUS BIOCHAR TYPES AS GREEN ADSORBENTS FOR RARE EARTH ELEMENT RECOVERY FROM AQUEOUS SOLUTIONS , Oluwaseun Victor Famobuwa

Selective Recovery of Various Critical Metals from Acid Mine Drainage Sludge , Gorkem Gecimli

Theses/Dissertations from 2023 2023

Development of A Hydrometallurgical Process for the Extraction of Cobalt, Manganese, and Nickel from Acid Mine Drainage Treatment Byproduct , Alejandro Agudelo Mira

Selective Recovery of Rare Earth Elements from Acid Mine Drainage Treatment Byproduct , Zeynep Cicek

Identification of Rockmass Deformation and Lithological Changes in Underground Mines by Using Slam-Based Lidar Technology , Francisco Eduardo Gil Hurtado

Analysis of the Brittle Failure Mechanism of Underground Stone Mine Pillars by Implementing Numerical Modeling in FLAC3D , Rosbel Jimenez

Analysis of the root causes of fatal injuries in the United States surface mines between 2008 and 2021. , Maria Fernanda Quintero

AUGMENTED REALITY AND MOBILE SYSTEMS FOR HEAVY EQUIPMENT OPERATORS IN SURFACE MINING , Juan David Valencia Quiceno

Theses/Dissertations from 2022 2022

Integrated Large Discontinuity Factor, Lamodel and Stability Mapping Approach for Stone Mine Pillar Stability , Mustafa Baris Ates

Noise Exposure Trends Among Violating Coal Mines, 2000 to 2021 , Hanna Grace Davis

Calcite depression in bastnaesite-calcite flotation system using organic acids , Emmy Muhoza

Investigation of Geomechanical Behavior of Laminated Rock Mass Through Experimental and Numerical Approach , Qingwen Shi

Static Liquefaction in Tailing Dams , Jose Raul Zela Concha

Experimental and Theoretical Investigation on the Initiation Mechanism of Low-Rank Coal's Self-Heating Process , Yinan Zhang

Development of an Entry-Scale Modeling Methodology to Provide Ground Reaction Curves for Longwall Gateroad Support Evaluation , Haochen Zhao

Size effect and anisotropy on the strength of shale under compressive stress conditions , Yun Zhao

Theses/Dissertations from 2021 2021

Evaluation of LIDAR systems for rock mass discontinuity identification in underground stone mines from 3D point cloud data , Mario Alejandro Bendezu de la Cruz

Implementing the Empirical Stone Mine Pillar Strength Equation into the Boundary Element Method Software LaModel , Samuel Escobar

Recovery of Phosphorus from Florida Phosphatic Waste Clay , Amir Eskanlou

Optimization of Operating Conditions and Design Parameters on Coal Ultra-Fine Grinding Through Kinetic Stirred Mill Tests and Numerical Modeling , Francisco Patino

The Effect of Natural Fractures on the Mechanical Behavior of Limestone Pillars: A Synthetic Rock Mass Approach Application , Mustafa Can Süner

Evaluation of Various Separation Techniques for the Removal of Actinides from A Rare Earth-Containing Solution Generated from Coarse Coal Refuse , Deniz Talan

Geology Oriented Loading Approach for Underground Coal Mines , Deniz Tuncay

Various Operational Aspects of the Extraction of Critical Minerals from Acid Mine Drainage and Its Treatment By-product , Zhongqing Xiao

Theses/Dissertations from 2020 2020

Adaptation of Coal Mine Floor Rating (CMFR) to Eastern U.S. Coal Mines , Sena Cicek

Upstream Tailings Dam - Liquefaction , Mladen Dragic

Development, Analysis and Case Studies of Impact Resistant Steel Sets for Underground Roof Fall Rehabilitation , Dakota D. Faulkner

The influence of spatial variance on rock strength and mechanism of failure , Danqing Gao

Fundamental Studies on the Recovery of Rare Earth Elements from Acid Mine Drainage , Xue Huang

Rational drilling control parameters to reduce respirable dust during roof bolting operations , Hua Jiang

Solutions to Some Mine Subsidence Research Challenges , Jian Yang

An Interactive Mobile Equipment Task-Training with Virtual Reality , Lazar Zujovic

Theses/Dissertations from 2019 2019

Fundamental Mechanism of Time Dependent Failure in Shale , Neel Gupta

A Critical Assessment on the Resources and Extraction of Rare Earth Elements from Acid Mine Drainage , Christopher R. Vass

Time-dependent deformation and associated failure of roof in underground mines , Yuting Xue

Theses/Dissertations from 2018 2018

Parametric Study of Coal Liberation Behavior Using Silica Grinding Media , Adewale Wasiu Adeniji

Three-dimensional Numerical Modeling Encompassing the Stability of a Vertical Gas Well Subjected to Longwall Mining Operation - A Case Study , Bonaventura Alves Mangu Bali

Shale Characterization and Size-effect study using Scanning Electron Microscopy and X-Ray Diffraction , Debashis Das

Behaviour Of Laminated Roof Under High Horizontal Stress , Prasoon Garg

Theses/Dissertations from 2017 2017

Optimization of Mineral Processing Circuit Design under Uncertainty , Seyed Hassan Amini

Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses , Thomas W. Edge II

A Photogrammetry Program for Physical Modeling of Subsurface Subsidence Process , Yujia Lian

An Area-Based Calculation of the Analysis of Roof Bolt Systems (ARBS) , Aanand Nandula

Developing and implementing new algorithms into the LaModel program for numerical analysis of multiple seam interactions , Mehdi Rajaeebaygi

Adapting Roof Support Methods for Anchoring Satellites on Asteroids , Grant B. Speer

Simulation of Venturi Tube Design for Column Flotation Using Computational Fluid Dynamics , Wan Wang

Theses/Dissertations from 2016 2016

Critical Analysis of Longwall Ventilation Systems and Removal of Methane , Robert B. Krog

Implementing the Local Mine Stiffness Calculation in LaModel , Kaifang Li

Development of Emission Factors (EFs) Model for Coal Train Loading Operations , Bisleshana Brahma Prakash

Nondestructive Methods to Characterize Rock Mechanical Properties at Low-Temperature: Applications for Asteroid Capture Technologies , Kara A. Savage

Mineral Asset Valuation Under Economic Uncertainty: A Complex System for Operational Flexibility , Marcell B. B. Silveira

A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges , Christopher R. Vass

Spontaneous Combustion of South American Coal , Brunno C. C. Vieira

Calibrating LaModel for Subsidence , Jian Yang

Theses/Dissertations from 2015 2015

Coal Quality Management Model for a Dome Storage (DS-CQMM) , Manuel Alejandro Badani Prado

Design Programs for Highwall Mining Operations , Ming Fan

Development of Drilling Control Technology to Reduce Drilling Noise during Roof Bolting Operations , Mingming Li

The Online LaModel User's & Training Manual Development & Testing , Christopher R. Newman

How to mitigate coal mine bumps through understanding the violent failure of coal specimens , Gamal Rashed

Theses/Dissertations from 2014 2014

Effect of biaxial and triaxial stresses on coal mine shale rocks , Shrey Arora

Stability Analysis of Bleeder Entries in Underground Coal Mines Using the Displacement-Discontinuity and Finite-Difference Programs , Xu Tang

Experimental and Theoretical Studies of Kinetics and Quality Parameters to Determine Spontaneous Combustion Propensity of U.S. Coals , Xinyang Wang

Bubble Size Effects in Coal Flotation and Phosphate Reverse Flotation using a Pico-nano Bubble Generator , Yu Xiong

Integrating the LaModel and ARMPS Programs (ARMPS-LAM) , Peng Zhang

Theses/Dissertations from 2013 2013

Column Flotation of Subbituminous Coal Using the Blend of Trimethyl Pentanediol Derivatives and Pico-Nano Bubbles , Jinxiang Chen

Applications of Surface and Subsurface Subsidence Theories to Solve Ground Control Problems , Biao Qiu

Calibrating the LaModel Program for Shallow Cover Multiple-Seam Mines , Morgan M. Sears

The Integration of a Coal Mine Emergency Communication Network into Pre-Mine Planning and Development , Mark F. Sindelar

Factors considered for increasing longwall panel width , Jack D. Trackemas

An experimental investigation of the creep behavior of an underground coalmine roof with shale formation , Priyesh Verma

Evaluation of Rope Shovel Operators in Surface Coal Mining Using a Multi-Attribute Decision-Making Model , Ivana M. Vukotic

Theses/Dissertations from 2012 2012

Calculating the Surface Seismic Signal from a Trapped Miner , Adeniyi A. Adebisi

Comprehensive and Integrated Model for Atmospheric Status in Sealed Underground Mine Areas , Jianwei Cheng

Production and Cost Assessment of a Potential Application of Surface Miners in Coal Mining in West Virginia , Timothy A. Nolan

The Integration of Geomorphic Design into West Virginia Surface Mine Reclamation , Alison E. Sears

Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining , Patricio G. Terrazas Prado

New Abutment Angle Concept for Underground Coal Mining , Ihsan Berk Tulu

Theses/Dissertations from 2011 2011

Experimental analysis of the post-failure behavior of coal and rock under laboratory compression tests , Dachao Neil Nie

The influence of interface friction and w/h ratio on the violence of coal specimen failure , Simon H. Prassetyo

Theses/Dissertations from 2010 2010

A risk management approach to pillar extraction in the Central Appalachian coalfields , Patrick R. Bucks

The Impacts of Longwall Mining on Groundwater Systems -- A Case of Cumberland Mine Panels B5 and B6 , Xinzhi Du

Evaluation of ultrafine spiral concentrators for coal cleaning , Meng Yang

Theses/Dissertations from 2009 2009

Development of a coal reserve GIS model and estimation of the recoverability and extraction costs , Chandrakanth Reddy Apala

Application and evaluation of spiral separators for fine coal cleaning , Zhuping Che

Weak floor stability in the Illinois Basin underground coal mines , Murali M. Gadde

Design of reinforced concrete seals for underground coal mines , Rajagopala Reddy Kallu

Employing laboratory physical modeling to study the radio imaging method (RIM) , Jun Lu

Influence of cutting sequence and time effects on cutters and roof falls in underground coal mine -- numerical approach , Anil Kumar Ray

Implementing energy release rate calculations into the LaModel program , Morgan M. Sears

Modeling PDC cutter rock interaction , Ihsan Berk Tulu

Analytical determination of strain energy for the studies of coal mine bumps , Qiang Xu

Improvement of the mine fire simulation program MFIRE , Lihong Zhou

Theses/Dissertations from 2008 2008

Program-assisted analysis of the transverse pressure capacity of block stoppings for mine ventilation control , Timothy J. Batchler

Analysis of factors affecting wireless communication systems in underground coal mines , David P. McGraw

Analysis of underground coal mine refuge shelters , Mickey D. Mitchell

Theses/Dissertations from 2007 2007

Dolomite flotation of high magnesium phosphate ores using fatty acid soap collectors , Zhengxing Gu

Evaluation of longwall face support hydraulic supply systems , Ted M. Klemetti II

Experimental studies of electromagnetic signals to enhance radio imaging method (RIM) , William D. Monaghan

Analysis of water monitoring data for longwall panels , Joseph R. Zirkle

Theses/Dissertations from 2006 2006

Measurements of the electrical properties of coal measure rocks , Nikolay D. Boykov

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Data Mining Thesis Ideas
Top 4 Trending Thesis Topics in Data Mining [Capstone Project Ideas]
Top 4 Trending Thesis Topics in Data Mining [Capstone Project Ideas]
140 Excellent Big Data Research Topics to Consider
PhD Thesis Topics in Data Mining (Thesis Writing Help)

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82 Data Mining Essay Topic Ideas & Examples
Data Mining Role in Companies. The increasing adoption of data mining in various sectors illustrates the potential of the technology regarding the analysis of data by entities that seek information crucial to their operations. We will write a custom essay specifically for you by our professional experts. 190 writers online.
105 Data Mining Essay Topic Ideas & Examples
If you are a student or a professional looking to write an essay on data mining, here are 105 topic ideas and examples to help you get started. The importance of data mining in today's business world. Ethical considerations in data mining. The impact of data mining on privacy.
data mining Latest Research Papers
The accurate average value is 74.05% of the existing COID algorithm, and our proposed algorithm has 77.21%. The average recall value is 81.19% and 89.51% of the existing and proposed algorithm, which shows that the proposed work efficiency is better than the existing COID algorithm. Download Full-text.
Latest Research and Thesis topics in Data Mining
Structure mining examines the data which is related to the structure of the website while usage mining examines data from the user's browser. The data collected through web mining is evaluated and analyzed using techniques like clustering, classification, and association. It is a very good topic for the thesis in data mining.
Data Mining Thesis Topics
Data Mining Thesis. Data Mining Thesis ideas and topics are drafted by us you can get unique , clean and informative thesis that gets you a higher grade. Data mining is one of the important domains that deals with the detection of unrecognized or hidden patterns. Encompassing the research methodology, we suggest an extensive summary based on a ...
Data Mining Latest Research Topics
Data mining is one of the prevalent domains which emerge rapidly with novel strategies, new plans and modern algorithms. Accompanied with the short explanations of their relevance and probable applications, we recommend multiple advanced and interesting research topics on the subject of data mining: Explainable AI in Data Mining.
Data Mining Dissertation Topics
Data Mining Dissertation Topics. The term "data mining" refers to an intelligent data lookup capacity that uses statistics-based algorithms and methodologies to find trends, patterns, links, and correlations within the collected data and records. Audio, Pictorial, Video, textual, online, and social media-based mining are only a few examples ...
Data Mining
Achieving Long Term Fairness through Curiosity Driven Reinforcement Learning: How intrinsic motivation influences fairness in algorithmic decision making. van der Wee, W. J. (Author), Pechenizkiy, M. (Supervisor 1), Gajane, P. (Supervisor 2) & Kapodistria, S. (Supervisor 2), 28 Aug 2023. Student thesis: Master.
(PDF) Trends in data mining research: A two-decade review using topic
Address: 20, Myasnitskaya Street, Moscow 101000, Russia. Abstract. This work analyzes the intellectual structure of data mining as a scientiﬁc discipline. T o do this, we use. topic analysis ...
PDF Data Mining Thesis Topics in Finland
information regarding degree topics stays up to date. 2.2 Data Mining Overview Data mining is the process of discovering patterns and relationships in large volumes of data by using methods from the areas of computer science, statistics and artificial intelligence [12]. Data mining is a general term and it can often be confusing. Moreover,
Data Mining for the Internet of Things: Literature Review and
A variety of researches focusing on knowledge view, technique view, and application view can be found in the literature. However, no previous effort has been made to review the different views of data mining in a systematic way, especially in nowadays big data [5-7]; mobile internet and Internet of Things [8-10] grow rapidly and some data mining researchers shift their attention from data ...
Dissertations / Theses: 'Data mining'
Consult the top 50 dissertations / theses for your research on the topic 'Data mining.'. Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
PDF The application of data mining methods
This thesis first introduces the basic concepts of data mining, such as the definition of data mining, its basic function, common methods and basic process, and two common data mining methods, classification and clustering. Then a data mining application in network is discussed in detail, followed by a brief introduction on data mining ...
Innovative Research Topics on Data Mining (Latest Titles)
Research Topics on Data Mining offer you creative ideas to prime your future brightly in research. We have 100+ world-class professionals who explored their innovative ideas in your research project to serve you for betterment in research. So We have conducted 500+ workshops throughout the world, and a large number of researchers and students ...
Trending Data Mining Thesis Topics
Integration of MapReduce, Amazon EC2, S3, Apache Spark, and Hadoop into data mining. These are the recent trends in data mining. We insist that you choose one of the topics that interest you the most. Having an appropriate content structure or template is essential while writing a thesis.
Data mining topics in the discipline of library and information science
The topic modeling result identified prevailing data mining related research topics in LIS, such as machine learning, deep learning, big data and among others. In addition, this study investigated the trends of popular topics in LIS over time in the recent decade.,This investigation is one of a few studies that empirically investigated the ...
Research Topics & Ideas: Data Science
If you're just starting out exploring data science-related topics for your dissertation, thesis or research project, you've come to the right place. In this post, we'll help kickstart your research by providing a hearty list of data science and analytics-related research ideas, including examples from recent studies.. PS - This is just the start…
Data Mining Research Topics for MS PhD
Data Mining Research Topics. I am sharing with you some of the research topics regarding data mining that you can choose for your research proposal for the thesis work of MS, or Ph.D. Degree. Categorizing the research into 4 categories in this tutorial . Industry-based research in data mining; Problem-based research in data mining
data mining
First, talk to your thesis advisor before committing to a project. They know better than I do. Secondly, just analyzing a new dataset using standard techniques doesn't make for a good masters thesis. Your project is expected to use some sort of novel approach.
Thesis Topics Related To Data Mining
Thesis Topics Related to Data Mining - Free download as PDF File (.pdf), Text File (.txt) or read online for free. The document discusses some of the challenges involved in writing a thesis on data mining topics. One challenge is selecting a relevant research area from the vast array of available data mining techniques and applications. Another difficulty is the significant time investment ...
14 Data Mining Projects With Source Code
In this data-centric world, data mining projects hold great importance in everyday life. It provides us a reliable source of resolving tough problems and different issues in this challenging world. Some of the benefits are: -. With the help of new and legacy systems, data mining helps in making well-informed decisions.
Latest Data Mining Projects Topics & Ideas
Matlab Projects. Information Security. iOS Projects. Artificial Intelligence. Embedded Projects. This list of data mining project topics has been complied to help students and researchers to get a jump start in their electronics development. Our developers constantly compile latest data mining project ideas and topics to help student learn more ...
Mining Engineering Graduate Theses and Dissertations
Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining, Patricio G. Terrazas Prado. PDF. New Abutment Angle Concept for Underground Coal Mining, Ihsan Berk Tulu. Theses/Dissertations from 2011 PDF. Experimental analysis of the post-failure behavior of coal and rock under laboratory compression tests, Dachao ...

82 Data Mining Essay Topic Ideas & Examples

105 Data Mining Essay Topic Ideas & Examples

data mining Recently Published Documents

Distance Based Pattern Driven Mining for Outlier Detection in High Dimensional Big Dataset

Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

Multi-objective economic load dispatch method based on data mining technology for large coal-fired power plants

A data mining analysis of COVID-19 cases in states of United States of America

Exploring distributed energy generation for sustainable development: A data mining approach

Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques

The Influence of E-book Teaching on the Motivation and Effectiveness of Learning Law by Using Data Mining Analysis

Intelligent Data Mining based Method for Efficient English Teaching and Cultural Analysis

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Achieving Long Term Fairness through Curiosity Driven Reinforcement Learning: How intrinsic motivation influences fairness in algorithmic decision making

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Data Mining Research Topics for MS PhD

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