Generating semantic annotations for frequent patterns with context analysis

Qiaozhu Mei, Dong Xin, Hong Cheng, Jiawei Man, Chengxiang Zhai

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

Abstract

As a fundamental data mining task, frequent pattern mining has widespread applications in many different domains. Research in frequent pattern mining has so far mostly focused on developing efficient algorithms to discover various kinds of frequent patterns, but little attention has been paid to the important next step - interpreting the discovered frequent patterns. Although some recent work has studied the compression and summarization of frequent patterns, the proposed techniques can only annotate a frequent pattern with non-semantical information (e.g. support), which provides only limited help for a user to understand the patterns. In this paper, we propose the novel problem of generating semantic annotations for frequent patterns. The goal is to annotate a frequent pattern with in-depth, concise, and structured information that can better Indicate the hidden meanings of the pattern. We propose a general approach to generate such an annotation for a frequent pattern by constructing its context model, selecting informative context indicators, and extracting representative transactions and semantically similar patterns. This general approach has potentially many applications such as generating a dictionarylike description for a pattern, finding synonym patterns, discovering semantic relations, and summarizing semantic classes of a set of frequent patterns. Experiments on different datasets show that our approach is effective in generating semantic pattern annotations.

Original languageEnglish (US)
Title of host publicationKDD 2006
Subtitle of host publicationProceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages337-346
Number of pages10
ISBN (Print)1595933395, 9781595933393
DOIs
StatePublished - Jan 1 2006
EventKDD 2006: 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - Philadelphia, PA, United States
Duration: Aug 20 2006Aug 23 2006

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume2006

Other

OtherKDD 2006: 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
CountryUnited States
CityPhiladelphia, PA
Period8/20/068/23/06

Keywords

  • Frequent pattern
  • Pattern annotation
  • Pattern context
  • Pattern semantic analysis

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Mei, Q., Xin, D., Cheng, H., Man, J., & Zhai, C. (2006). Generating semantic annotations for frequent patterns with context analysis. In KDD 2006: Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 337-346). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 2006). Association for Computing Machinery. https://doi.org/10.1145/1150402.1150441