Empirical evaluation of interest-level criteria

Sigal Sahar, Yishay Mansour

Research output: Contribution to journalConference articlepeer-review


Efficient association rule mining algorithms already exist, but as the size of databases increases, the number of patterns mined by the algorithms increases to such extent that their manual evaluation becomes impractical. An empirical evaluation is conducted using several databases, to discover whether the ranking performed by the various criteria is similar or easily distinguishable. It reveals that most of the rules found by the comparably strict parameters ranked highly according to the interestingness criteria when using lax parameters.

Original languageEnglish
Pages (from-to)63-74
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 1999
EventProceedings of the 1999 Data Mining and Knowledge Discovery: Theory, Tools, and Technology - Orlando, FL, USA
Duration: 5 Apr 19996 Apr 1999


Dive into the research topics of 'Empirical evaluation of interest-level criteria'. Together they form a unique fingerprint.

Cite this