Sampling minimal frequent boolean (DNF) patterns

Geng Li, Mohammed J. Zaki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We tackle the challenging problem of mining the simplest Boolean patterns from categorical datasets. Instead of complete enumeration, which is typically infeasible for this class of patterns, we develop effective sampling methods to extract a representative subset of the minimal Boolean patterns (in disjunctive normal form - DNF). We make both theoretical and practical contributions, which allow us to prune the search space based on provable properties. Our approach can provide a near-uniform sample of the minimal DNF patterns. We also show that the mined minimal DNF patterns are very effective when used as features for classification.

Original languageEnglish
Title of host publicationProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages87-95
Number of pages9
DOIs
Publication statusPublished - 14 Sep 2012
Externally publishedYes
Event18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 - Beijing, China
Duration: 12 Aug 201216 Aug 2012

Other

Other18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012
CountryChina
CityBeijing
Period12/8/1216/8/12

Fingerprint

Set theory
Sampling

Keywords

  • boolean expression patterns
  • minimal generator
  • pattern-based classification
  • sampling

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Li, G., & Zaki, M. J. (2012). Sampling minimal frequent boolean (DNF) patterns. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 87-95) https://doi.org/10.1145/2339530.2339547

Sampling minimal frequent boolean (DNF) patterns. / Li, Geng; Zaki, Mohammed J.

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. p. 87-95.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, G & Zaki, MJ 2012, Sampling minimal frequent boolean (DNF) patterns. in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 87-95, 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012, Beijing, China, 12/8/12. https://doi.org/10.1145/2339530.2339547
Li G, Zaki MJ. Sampling minimal frequent boolean (DNF) patterns. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. p. 87-95 https://doi.org/10.1145/2339530.2339547
Li, Geng ; Zaki, Mohammed J. / Sampling minimal frequent boolean (DNF) patterns. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012. pp. 87-95
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