WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR

Query expansion (QE) is the process of reformulating a query to improve retrieval performance. Most of the times user's query contains ambiguous terms which adds relevant as well as irrelevant terms to the query after applying current query expansion methods. This results in to low precision. T...

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Main Authors: Kanika Mittal, Amita Jain
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2015-01-01
Series:ICTACT Journal on Soft Computing
Subjects:
Online Access:http://ictactjournals.in/paper/IJSC_Splissue_Jan2015_Paper_3_896_to_904.pdf
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spelling doaj-601897c571704dcab173159df6ce61e42020-11-25T00:21:14ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562015-01-0152896904WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATORKanika Mittal0Amita Jain1Department of Computer Science and Engineering, Bhagwan Parshuram Institute of Technology, IndiaDepartment of Computer Science, Ambedkar Institute of Advanced Communication Technologies & Research, IndiaQuery expansion (QE) is the process of reformulating a query to improve retrieval performance. Most of the times user's query contains ambiguous terms which adds relevant as well as irrelevant terms to the query after applying current query expansion methods. This results in to low precision. The existing query expansion techniques do not consider the context of the ambiguous words present in the user's query. This paper presents a method for resolving the correct sense of the ambiguous terms present in the query by determining the similarity of the ambiguous term with the other terms in the query and then assigning weights to the similarity. The weights to the similarity measures of the terms are assigned on the basis of decreasing order of distance to the ambiguous term. An aggregated similarity score based on the assigned weights is calculated using Ordered weighted averaging operator (OWA) for each sense of the ambiguous term and the sense having highest similarity score will be considered as the most appropriate sense for the ambiguous term. After then, the query is expanded by taking an implicit feedback from user and adding terms related to the corresponding sense and hence optimizing the query expansion process.http://ictactjournals.in/paper/IJSC_Splissue_Jan2015_Paper_3_896_to_904.pdfQuery ExpansionNatural Language ProcessingInformation RetrievalWord Sense DisambiguationWordNetOWA Operator
collection DOAJ
language English
format Article
sources DOAJ
author Kanika Mittal
Amita Jain
spellingShingle Kanika Mittal
Amita Jain
WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
ICTACT Journal on Soft Computing
Query Expansion
Natural Language Processing
Information Retrieval
Word Sense Disambiguation
WordNet
OWA Operator
author_facet Kanika Mittal
Amita Jain
author_sort Kanika Mittal
title WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
title_short WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
title_full WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
title_fullStr WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
title_full_unstemmed WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR
title_sort word sense disambiguation method using semantic similarity measures and owa operator
publisher ICT Academy of Tamil Nadu
series ICTACT Journal on Soft Computing
issn 0976-6561
2229-6956
publishDate 2015-01-01
description Query expansion (QE) is the process of reformulating a query to improve retrieval performance. Most of the times user's query contains ambiguous terms which adds relevant as well as irrelevant terms to the query after applying current query expansion methods. This results in to low precision. The existing query expansion techniques do not consider the context of the ambiguous words present in the user's query. This paper presents a method for resolving the correct sense of the ambiguous terms present in the query by determining the similarity of the ambiguous term with the other terms in the query and then assigning weights to the similarity. The weights to the similarity measures of the terms are assigned on the basis of decreasing order of distance to the ambiguous term. An aggregated similarity score based on the assigned weights is calculated using Ordered weighted averaging operator (OWA) for each sense of the ambiguous term and the sense having highest similarity score will be considered as the most appropriate sense for the ambiguous term. After then, the query is expanded by taking an implicit feedback from user and adding terms related to the corresponding sense and hence optimizing the query expansion process.
topic Query Expansion
Natural Language Processing
Information Retrieval
Word Sense Disambiguation
WordNet
OWA Operator
url http://ictactjournals.in/paper/IJSC_Splissue_Jan2015_Paper_3_896_to_904.pdf
work_keys_str_mv AT kanikamittal wordsensedisambiguationmethodusingsemanticsimilaritymeasuresandowaoperator
AT amitajain wordsensedisambiguationmethodusingsemanticsimilaritymeasuresandowaoperator
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