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Sentence similarity measurement based on shallow parsing

  • Lin Li*
  • , Yiming Zhou
  • , Boqiu Yuan
  • , Jun Wang
  • , Xia Hu
  • *Corresponding author for this work

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

Abstract

The paper proposes a novel method to determine sentence similarities. First two compared sentences are parsed by shallow-parsing and all noun phrases, verb phrases and preposition phrases of each sentence are extracted. Then the similarity between each kind of phrases is calculated based on a semantic vector method. The overall sentence similarity is defined as a combination of semantic similarities of the three kinds of phrases. Experiments show that the proposed method has a high performance in F-measure (81.6%) and Recall (97.4%).

Original languageEnglish
Title of host publication6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Pages487-491
Number of pages5
DOIs
StatePublished - 2009
Event6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009 - Tianjin, China
Duration: 14 Aug 200916 Aug 2009

Publication series

Name6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Volume7

Conference

Conference6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009
Country/TerritoryChina
CityTianjin
Period14/08/0916/08/09

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