A framework for automatic topic discovery on subWebs

Ok Ran Jeong, Seunghwa Lee, Eunseok Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

As the amount of available information on the internet has become huge, it has become increasingly difficult for users to find information that is relevant to their needs. This has necessitated automated tools that can help users find information they need quickly and easily. In this paper, we propose a methodology for automatically finding topics of interest to users through related subWebs (subdirectories of a Web site). The methodology consists of a subWeb mining framework that performs parsing, clustering, and analysis of subWebs, and a ranking algorithm for the clusters.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages332-337
Number of pages6
DOIs
StatePublished - 2008
Event5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 - Jinan, Shandong, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Volume2

Conference

Conference5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Country/TerritoryChina
CityJinan, Shandong
Period18/10/0820/10/08

Keywords

  • Ranking algorithm
  • SubWeb
  • Topic discovery
  • Web mining

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