A new method of clustering search results using frequent itemsets with graph structures

I. Fang Su, Yu Chi Chung, Chiang Lee, Xuanyou Lin

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

Abstract

The representation of search results from the World Wide Web has received considerable attention in the database research community. Systems have been proposed for clustering search results into meaningful semantic categories for presentation to the end user. This paper presents a novel clustering algorithm, which is based on the concept of frequent itemsets mining over a graph structure, to efficiently generate search result clusters. The performance study reveals that the algorithm was highly efficient and significantly outperformed previous approaches in clustering search results.

Original languageEnglish
Title of host publicationIT Convergence and Services, ITCS 2011 and IRoA 2011
Pages87-97
Number of pages11
DOIs
Publication statusPublished - 2012 Jan 1
Event3rd International Conference on Information Technology Convergence and Services, ITCS 2011 and 2011 FTRA International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2011 - Gwangju, Korea, Republic of
Duration: 2011 Oct 202011 Oct 22

Publication series

NameLecture Notes in Electrical Engineering
Volume107 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other3rd International Conference on Information Technology Convergence and Services, ITCS 2011 and 2011 FTRA International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications, IRoA 2011
CountryKorea, Republic of
CityGwangju
Period11-10-2011-10-22

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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