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Using WordNet to determine semantic similarity of words

نویسنده:
مصطفی قاضی زاده احسائی
,
محمود نقیب زاده
,
S.Ehsan Yasrebi
,
Mostafa GhazizadehAhsaee
,
Mahmoud Naghibzadeh
سال
: 2010
چکیده: Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. Similarity of words in WordNet is also considered in recent researches. One of the new researches that uses WordNet, has calculated similarity between each two words by considering Depth of Subsumer of the words and Shortest Path between them.In this paper we have improved semantic similarity measure by modifying transfer functions of the previous research. We have tuned parameters of the transfer functions using particle swarm optimization. Based on our experimental results on a benchmark set by human similarity judgment, the resultant correlation has been improved
یو آر آی: https://libsearch.um.ac.ir:443/fum/handle/fum/3378773
کلیدواژه(گان): Semantic similarity,WordNet,natural language processing,information and knowledge retrieval
کالکشن :
  • ProfDoc
  • نمایش متادیتا پنهان کردن متادیتا
  • آمار بازدید

    Using WordNet to determine semantic similarity of words

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contributor authorمصطفی قاضی زاده احسائیen
contributor authorمحمود نقیب زادهen
contributor authorS.Ehsan Yasrebien
contributor authorMostafa GhazizadehAhsaeefa
contributor authorMahmoud Naghibzadehfa
date accessioned2020-06-06T14:00:45Z
date available2020-06-06T14:00:45Z
date copyright12/4/2010
date issued2010
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/3378773
description abstractWord and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. Similarity of words in WordNet is also considered in recent researches. One of the new researches that uses WordNet, has calculated similarity between each two words by considering Depth of Subsumer of the words and Shortest Path between them.In this paper we have improved semantic similarity measure by modifying transfer functions of the previous research. We have tuned parameters of the transfer functions using particle swarm optimization. Based on our experimental results on a benchmark set by human similarity judgment, the resultant correlation has been improveden
languageEnglish
titleUsing WordNet to determine semantic similarity of wordsen
typeConference Paper
contenttypeExternal Fulltext
subject keywordsSemantic similarityen
subject keywordsWordNeten
subject keywordsnatural language processingen
subject keywordsinformation and knowledge retrievalen
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1020401.html
conference titleFifth international Symposium on telecommunicationen
conference locationتهرانfa
identifier articleid1020401
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