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A clustering algorithm of no-word-segmentation for Chinese search engine results

  • Beihang University

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

Abstract

Along with information on the Internet increasing dramatically, People usually search and locate information that they needed by search engines. Clustering search engine results is an effective method to help people select information needed from the list of search engine results. The paper presents a clustering algorithm of no-word-segmentation for Chinese search engine results (CANWS). The algorithm firstly preprocesses the search engine results and then computes the similarities of the results based on the same sub-string. Lastly it clusters the results based on the similarity matrix. The paper also gives test and analysis of the algorithm performance by experiments.

Original languageEnglish
Title of host publication3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007
PublisherIEEE Computer Society
Pages258-261
Number of pages4
ISBN (Print)0769530079, 9780769530079
DOIs
StatePublished - 2007
Event3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007 - Xi'an, China
Duration: 29 Oct 200731 Oct 2007

Publication series

Name3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007

Conference

Conference3rd International Conference on Semantics, Knowledge, and Grid, SKG 2007
Country/TerritoryChina
CityXi'an
Period29/10/0731/10/07

Keywords

  • Clustering algorithm
  • Clustering results
  • Search engine results
  • Similarity algorithm

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