Maintenance of fast updated frequent trees for record deletion based on prelarge concepts

Chun Wei Lin, Tzung Pei Hong, Wen Hsiang Lu, Chih Hung Wu

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

2 Citations (Scopus)

Abstract

The frequent pattern tree (FP-tree) is an efficient data structure for association-rule mining without generation of candidate itemsets. It, however, needed to process all transactions in a batch way. In the past, we proposed the Fast Updated FP-tree (FUFP-tree) structure to efficientiy handle the newly inserted transactions in incremental mining. In this paper, we attempt to modify the FUFP-tree maintenance based on the concept of pre-large itemsets for efficiently handling deletion of records. Pre-large itemsets are defined by a lower support threshold and an upper support threshold. The proposed approach can thus achieve a good execution time for tree maintenance especially when each time a small number of records are deleted. Experimental results also show that the proposed Pre-FUFP deletion algorithm has a good performance for incrementally handling deleted records.

Original languageEnglish
Title of host publicationNew Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
PublisherSpringer Verlag
Pages675-684
Number of pages10
ISBN (Print)9783540733225
DOIs
Publication statusPublished - 2007 Jan 1
Event20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007 - Kyoto, Japan
Duration: 2007 Jun 262007 Jun 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4570 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
CountryJapan
CityKyoto
Period07-06-2607-06-29

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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