1st Edition

Data Mining Technologies, Techniques, Tools, and Trends

By Bhavani Thuraisingham Copyright 1999
    288 Pages
    by CRC Press

    288 Pages
    by CRC Press

    Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges.

    Three parts divide Data Mining:

  • Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining
  • Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information
  • Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues.

    This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence.

    Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.
  • Introduction Database Systems Data Warehousing Some Other Technologies for Data Mining Architectural Support for Data Mining Data Mining from Start to Finish Data Mining Outcomes, Approaches, and Techniques Logic Programming as a Data Mining Technique Data Mining Tools Mining Distributed, Heterogeneous, and Legacy Databases Data Mining on Multimedia Data Data Mining and the World Wide Web Security and Privacy Issues of Data Mining Metadata Aspects of Mining Summary and Directions References Appendices Data Management Artificial Intelligence


    Bhavani Thuraisingham