Paraphrase Detection using String Similarity with Synonyms

This paper presents an approach to enhance text similarity using synonyms for paraphrase detection. Paraphrase detection detects sentences or texts with similar meaning. Synonym of words can help in paraphrase detection. However, considering synonyms for all the text in the comparison posted extra c...

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Main Authors: Lee, Jun Choi, Cheah, Yu-N
Format: Conference or Workshop Item
Language:English
Published: 2015
Subjects:
Online Access:http://ir.unimas.my/id/eprint/13241/7/Paraphrase%20Detection%20using%20String%20Similarity%20with%20Synonyms%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/13241/
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spelling my.unimas.ir.132412016-08-29T20:09:49Z http://ir.unimas.my/id/eprint/13241/ Paraphrase Detection using String Similarity with Synonyms Lee, Jun Choi Cheah, Yu-N QA75 Electronic computers. Computer science This paper presents an approach to enhance text similarity using synonyms for paraphrase detection. Paraphrase detection detects sentences or texts with similar meaning. Synonym of words can help in paraphrase detection. However, considering synonyms for all the text in the comparison posted extra computational task in the process. This study introduces a simpler approach in considering synonyms in text similarity. The proposed approach is able to be adopted in any term-based text similarity metrics for paraphrase detection. The proposed approach is evaluated using the Microsoft Research Paraphrase Corpus. The evaluation show better result compares to original similarity metrics and reasonable result compares to other selected paraphrase detection approaches in previous studies 2015-10-15 Conference or Workshop Item PeerReviewed text en http://ir.unimas.my/id/eprint/13241/7/Paraphrase%20Detection%20using%20String%20Similarity%20with%20Synonyms%20%28abstract%29.pdf Lee, Jun Choi and Cheah, Yu-N (2015) Paraphrase Detection using String Similarity with Synonyms. In: Fourth Asian Conference on Information Systems, ACIS 2015, 15-16 October 2015, Holiday Inn Resort Penang.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Lee, Jun Choi
Cheah, Yu-N
Paraphrase Detection using String Similarity with Synonyms
description This paper presents an approach to enhance text similarity using synonyms for paraphrase detection. Paraphrase detection detects sentences or texts with similar meaning. Synonym of words can help in paraphrase detection. However, considering synonyms for all the text in the comparison posted extra computational task in the process. This study introduces a simpler approach in considering synonyms in text similarity. The proposed approach is able to be adopted in any term-based text similarity metrics for paraphrase detection. The proposed approach is evaluated using the Microsoft Research Paraphrase Corpus. The evaluation show better result compares to original similarity metrics and reasonable result compares to other selected paraphrase detection approaches in previous studies
format Conference or Workshop Item
author Lee, Jun Choi
Cheah, Yu-N
author_facet Lee, Jun Choi
Cheah, Yu-N
author_sort Lee, Jun Choi
title Paraphrase Detection using String Similarity with Synonyms
title_short Paraphrase Detection using String Similarity with Synonyms
title_full Paraphrase Detection using String Similarity with Synonyms
title_fullStr Paraphrase Detection using String Similarity with Synonyms
title_full_unstemmed Paraphrase Detection using String Similarity with Synonyms
title_sort paraphrase detection using string similarity with synonyms
publishDate 2015
url http://ir.unimas.my/id/eprint/13241/7/Paraphrase%20Detection%20using%20String%20Similarity%20with%20Synonyms%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/13241/
_version_ 1644511609879527424
score 13.15806