Mining weighted partial periodic patterns

Kung Jiuan Yang, Tzung Pei Hong, Yuh Min Chen, Guo Cheng Lan

Research output: Chapter in Book/Report/Conference proceedingChapter


In the data mining area, partial periodic pattern mining has become an important issue in many business applications. Although weighted sequential pattern mining algorithms have been widely discussed, until now, there is no further discussion in the field of weighed partial periodic pattern mining. Thus, this work introduces a new research issue, named weighted partial periodic pattern mining, which considers the individual significances of events in an event sequence. In addition, a projection-based mining algorithm is presented to effectively handle the weighted partial periodic pattern mining problem. The experimental results show the proposed algorithm is efficient.

Original languageEnglish
Title of host publicationSpringer Proceedings in Complexity
Number of pages8
Publication statusPublished - 2013 Jan 1

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

All Science Journal Classification (ASJC) codes

  • Applied Mathematics
  • Modelling and Simulation
  • Computer Science Applications


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