Mining pure patterns in texts

Yasuhiro Yamada, Tetsuya Nakatoh, Kensuke Baba, Daisuke Ikeda

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

3 Citations (Scopus)

Abstract

We herein investigate finding unusual patterns from a given string as a text. In the present paper, the pattern is expressed as a substring of the string. The natural assumption with respect to the frequency of a pattern is that the shorter the length of the pattern, the larger the frequency of the pattern. We define a pattern to be pure if the frequencies of all of the substrings of the pattern are the same as the frequency of the pattern. This means that the substrings appear only within the pattern in the string. This condition is in contrast to the natural assumption. The present paper proposes three statistics for quantifying the purity of a pattern, i.e., probability, entropy, and difference, which are calculated based on the frequency of the pattern and its substrings. Experiments using DNA sequences reveal that patterns with large probability correspond to the features of the sequences.

Original languageEnglish
Title of host publicationProceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012
Pages285-290
Number of pages6
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012 - Fukuoka, Japan
Duration: Sept 20 2012Sept 22 2012

Publication series

NameProceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012

Conference

Conference1st IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012
Country/TerritoryJapan
CityFukuoka
Period9/20/129/22/12

Keywords

  • Pattern discovery
  • Pure pattern
  • Text mining

ASJC Scopus subject areas

  • Information Systems

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