Mining optimized association rules for numeric attributes

Takeshi Fukuda, Yasuhiko Morimoto, Shinichi Morishita, Takeshi Tokuyama

Research output: Contribution to conferencePaper

132 Citations (Scopus)

Abstract

This study is aimed at realizing a system that automatically finds appropriate ranges for numeric attributes in a given huge database. The study mainly focuses on computing two optimized ranges: one that maximizes the support on the condition that the confidence ratio is at least a given threshold value, and another that maximizes the confidence ratio on the condition that the support is at least a given threshold number. Using techniques from computational geometry, presented are novel algorithms that compute the optimized ranges in linear time if the data are sorted. Tests show the implementation to be fast not only in theory but also in practice.

Original languageEnglish
Pages182-191
Number of pages10
DOIs
Publication statusPublished - 1996
EventProceedings of the 1996 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, PODS - Montreal, Can
Duration: 1996 Jun 31996 Jun 5

Other

OtherProceedings of the 1996 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, PODS
CityMontreal, Can
Period96/6/396/6/5

ASJC Scopus subject areas

  • Engineering(all)

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    Fukuda, T., Morimoto, Y., Morishita, S., & Tokuyama, T. (1996). Mining optimized association rules for numeric attributes. 182-191. Paper presented at Proceedings of the 1996 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, PODS, Montreal, Can, . https://doi.org/10.1145/237661.237708