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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| Format: | Article |
| Language: | English |
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ICT Academy of Tamil Nadu
2015-01-01
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| Series: | ICTACT Journal on Soft Computing |
| Subjects: | |
| Online Access: | http://ictactjournals.in/paper/IJSC_Splissue_Jan2015_Paper_3_896_to_904.pdf |
| _version_ | 1818572164023975936 |
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| author | Kanika Mittal Amita Jain |
| author_facet | Kanika Mittal Amita Jain |
| author_sort | Kanika Mittal |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-14T18:53:33Z |
| format | Article |
| id | doaj.art-601897c571704dcab173159df6ce61e4 |
| institution | Directory Open Access Journal |
| issn | 0976-6561 2229-6956 |
| language | English |
| last_indexed | 2024-12-14T18:53:33Z |
| publishDate | 2015-01-01 |
| publisher | ICT Academy of Tamil Nadu |
| record_format | Article |
| series | ICTACT Journal on Soft Computing |
| spelling | doaj.art-601897c571704dcab173159df6ce61e42022-12-21T22:51:09ZengICT 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 |
| 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 |
| title | 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_short | WORD SENSE DISAMBIGUATION METHOD USING SEMANTIC SIMILARITY MEASURES AND OWA OPERATOR |
| title_sort | word sense disambiguation method using semantic similarity measures and owa operator |
| 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 |