Research Topics on Data Mining

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 those who explored their innovative ideas in your research project to serve you for betterment in research. We have conducted 500+ workshops throughout the world and large number of researchers and students benefited by our research. We often provide high quality topics and ideas through our online services for researchers and students. Nearly 10000+ projects are developed by our experienced programmer 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 have tie-up with authorised universities and colleges to guide for the projects and research. Our alumini giving idea about most recent concepts which help us to attained world top most position in research. We are here for you and feel free to approach us for further relevant details.

Research 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 most recent topics in data mining. Data mining is the computing process of discovering patterns in large datasets and establish the relationships to solve the problems. You can approach as with any topic we can provide you 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 the 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 distributed mining algorithms

  • Data mining and society

 -Data mining with social impacts

 -Data mining with privacy-preserving

 -Data mining for invisible

  • Efficiency and Scalability

 -Scalability and efficiency of data mining algorithms

 -Incremental, stream, distributed and parallel mining methods

  • Diversity of data types

 -Global, mining dynamic and networked data repositories

 -Handling complex types of data

  • Mining multi-agent data and distributed data mining
  • Dealing with cost-sensitive, non-static and unbalance data
  • Process related problems in data mining
  • Scaling up for high speed data streams and high dimensional data
  • Creating a unifying theory of data mining
  • Environmental and biological problems in data mining
  • Privacy and 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 web data mining
  • Scientific data mining
  • Dependable real time data mining
  • Symbolic data mining
  • Geospatial contrast mining
  • Bio-Inspired 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 for data mining (CRISP-DM)
  • Deep neural network learning
  • Efficient ML and DM techniques
  • Planet enlists machine learning
  • Quantum machine learning
  • SAPMachine Learning
  • NeuroRule : Connectionistapproach
  • Joao Gama machine learning
  • Adaptive synthetic samplingapproach
  • Integrated and cross-disciplinaryapproach
  • One-class SVMapproach
  • DataMining Practical Machine Learning Tools and Techniques
  • learninganalytics and machine learning techniques
  • kernel-based learning methods
  • human mental models and machine-learned models
  • data fusion approach

Recent Real Time Applications:

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

Latest Research Topics:

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

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