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Data Mining Techniques for Associations, Clustering and Classification

  • Charu C. Aggarwal
  • Philip S. Yu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1574)

Abstract

This paper provides a survey of various data mining techniques for advanced database applications. These include association rule generation, clustering and classification. With the recent increase in large online repositories of information, such techniques have great importance. The focus is on high dimensional data spaces with large volumes of data. The paper discusses past research on the topic and also studies the corresponding algorithms and applications.

Keywords

Association Rule Class Label Association Rule Mining Data Mining Technique Split Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Charu C. Aggarwal
    • 1
  • Philip S. Yu
    • 1
  1. 1.IBM T. J. Watson Research CenterYorktown HeightsUSA

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