Analyzing the Subjective Interestingness of Association Rules

@article{Liu2000AnalyzingTS,
  title={Analyzing the Subjective Interestingness of Association Rules},
  author={Bing Liu and Wynne Hsu and Shu Chen and Yiming Ma},
  journal={IEEE Intelligent Systems},
  year={2000},
  volume={15},
  pages={47-55}
}
Association rules are a class of important regularities in databases. They are found to be very useful in practical applications. However, association rule mining algorithms tend to produce a huge number of rules, most of which are of no interest to the user. Due to the large number of rules, it is very diff icult for the user to analyze them manually in order to identify those truly interesting ones. In this paper, we propose a new approach to assist the user in finding interesting rules (in… CONTINUE READING
Highly Influential
This paper has highly influenced a number of papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 259 citations. REVIEW CITATIONS

2 Figures & Tables

Topics

Statistics

0102030'00'02'04'06'08'10'12'14'16'18
Citations per Year

259 Citations

Semantic Scholar estimates that this publication has 259 citations based on the available data.

See our FAQ for additional information.