A novel web usage mining method - Mining and clustering of DAG access patterns considering page browsing time

Koichiro Mihara*, Masahiro Terabe, Kazuo Hashimoto

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

In this paper, we propose a novel method to analyze web access logs. The proposed method defines a web access pattern as a DAG with page browsing time, and extracts the patterns using the closed frequent embedded DAG mining algorithm, DIGDAG. The proposed method succeeds in extracting as small number of patterns as necessary minimum, and enables more efficient analysis by clustering the extracted results.

Original languageEnglish
Title of host publicationWEBIST 2008 - 4th International Conference on Web Information Systems and Technologies, Proceedings
Pages313-320
Number of pages8
Publication statusPublished - 2008
Externally publishedYes
EventWEBIST 2008 - 4th International Conference on Web Information Systems and Technologies - Funchal, Madeira, Portugal
Duration: 2008 May 42008 May 7

Publication series

NameWEBIST 2008 - 4th International Conference on Web Information Systems and Technologies, Proceedings
Volume2

Conference

ConferenceWEBIST 2008 - 4th International Conference on Web Information Systems and Technologies
Country/TerritoryPortugal
CityFunchal, Madeira
Period08/5/408/5/7

Keywords

  • Closed frequent embedded DAG mining
  • Clustering
  • Page browsing time
  • Web access log analysis
  • Web usage mining

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management

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