Incrementally fast updated sequential pattern trees

Tzung Pei Hong, Hsin Yi Chen, Chun Wei Lin, Sheng-Tun Li

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

5 Citations (Scopus)

Abstract

In the past, the FUFP-tree maintenance algorithm is proposed to efficiently handle the association rules in incremental mining. In this paper, we attempt to modify the FUFP-tree maintenance algorithm for maintaining sequential patterns based on the concept of pre-large sequences to reduce the need for rescanning original databases in incremental mining. A fast updated sequential pattern trees (FUSP trees) structure and the maintenance algorithm are proposed, which makes the tree update process become easier. It does not require rescanning original customer sequences until the accumulative amount of newly added customer sequences exceed a safety bound, which depends on database size. The proposed approach thus becomes efficiently and effectively for handling newly added customer sequences.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Pages3991-3996
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 23
Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China
Duration: 2008 Jul 122008 Jul 15

Publication series

NameProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Volume7

Other

Other7th International Conference on Machine Learning and Cybernetics, ICMLC
CountryChina
CityKunming
Period08-07-1208-07-15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

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