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A Query-Driven Interesting Rule Discovery Using Associations and Spanning Operations

  • Jong P. Yoon
  • Larry Kerschberg
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 95)

Abstract

In practice, users may often want interesting rules that are also related with user goals . This paper describes a technique of mining useful rules both interesting and related to user goals. According to the degree of relevancy to a user goal, a database can be divided into the five views: from the view positively related to the user goal to the view unrelated. To each such view, our novel technique of data mining can be applied. The union and join operations in SQL, unlike the traditional approaches which apply association and prunning operations to one view, are applied to one or more of those views. While the pattern association operation joins patterns over the different attributes, the pattern spanning operation unions patterns over the same attributes. The combination of two operations keeps both confidence and supportiveness measures together, and differenciation of query views enables us to produce the desired level of interestingness and relevancy.

Keywords

Data Mining Association Rule Point Pattern Pattern Association Union Operation 
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 2002

Authors and Affiliations

  • Jong P. Yoon
    • 1
  • Larry Kerschberg
    • 2
  1. 1.The Center for Advanced Computer StudiesUniversity of Louisiana at LafayetteLafayetteUSA
  2. 2.Department of Information and Software EngineeringGeorge Mason UniversityFairfaxUSA

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