An enhanced data mining life cycle

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Data mining projects are complex and can have a high failure rate. In order to improve project management and success rates of such projects a life cycle is vital to the overall success of the project. This paper reports on a research project that was concerned with the life cycle development for data mining projects, its team members and their role. The paper provides a detailed view of the design and development of the data mining life cycle called DMLC. The life cycle aims to support all members of data mining project teams as well as IT managers and academic researchers and may improve project success rates and strategic decision support. An extensive analysis of eight life cycles leads to a list of advantages, disadvantages, and characteristics of the life cycles. This is extended and generates a conglomerate of several guidelines which serve as the foundation for the development of a new generic data mining life cycle. A detailed study of the human resources involved in a data mining project enhances the DMLC.

    Original languageEnglish
    Title of host publication2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
    Pages109-117
    Number of pages9
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Nashville, TN, United States
    Duration: 30 Mar 20092 Apr 2009

    Publication series

    Name2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings

    Conference

    Conference2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009
    Country/TerritoryUnited States
    CityNashville, TN
    Period30/03/092/04/09

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