MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING

This paper investigates the use of clustering and lexical chains to produce coherent summaries of multiple documents in text format to generate an indicative, less redundant summary. The summary is designed as per user’s requirement of conciseness i.e., the documents are summarized according to the...

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Main Authors: S. Saraswathi, R. Arti
Format: Article
Language:English
Published: ICT Academy of Tamil Nadu 2010-07-01
Series:ICTACT Journal on Soft Computing
Subjects:
Online Access:http://ictactjournals.in/paper/ijsc4_page_23-29.pdf
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author S. Saraswathi
R. Arti
author_facet S. Saraswathi
R. Arti
author_sort S. Saraswathi
collection DOAJ
description This paper investigates the use of clustering and lexical chains to produce coherent summaries of multiple documents in text format to generate an indicative, less redundant summary. The summary is designed as per user’s requirement of conciseness i.e., the documents are summarized according to the percentage input by the user. For achieving the above, various clustering techniques are used. Clustering is done at two levels, one at single document level and then at multi-document level. The clustered sentences are scored based on five different methods and lexically linked to produce the final summary in a text document.
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spelling doaj.art-367887c844234186bf53c5447982cd1c2022-12-21T17:33:37ZengICT Academy of Tamil NaduICTACT Journal on Soft Computing0976-65612229-69562010-07-01112329MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAININGS. Saraswathi0R. Arti1Department of Information Technology, Pondicherry Engineering College, Pondicherry, IndiaMicrosoft R&D India Private Limited, Hyderabad, IndiaThis paper investigates the use of clustering and lexical chains to produce coherent summaries of multiple documents in text format to generate an indicative, less redundant summary. The summary is designed as per user’s requirement of conciseness i.e., the documents are summarized according to the percentage input by the user. For achieving the above, various clustering techniques are used. Clustering is done at two levels, one at single document level and then at multi-document level. The clustered sentences are scored based on five different methods and lexically linked to produce the final summary in a text document.http://ictactjournals.in/paper/ijsc4_page_23-29.pdfLexical ChainingPrecisionHierarchical ClusteringRecall
spellingShingle S. Saraswathi
R. Arti
MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
ICTACT Journal on Soft Computing
Lexical Chaining
Precision
Hierarchical Clustering
Recall
title MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
title_full MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
title_fullStr MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
title_full_unstemmed MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
title_short MULTI-DOCUMENT TEXT SUMMARIZATION USING CLUSTERING TECHNIQUES AND LEXICAL CHAINING
title_sort multi document text summarization using clustering techniques and lexical chaining
topic Lexical Chaining
Precision
Hierarchical Clustering
Recall
url http://ictactjournals.in/paper/ijsc4_page_23-29.pdf
work_keys_str_mv AT ssaraswathi multidocumenttextsummarizationusingclusteringtechniquesandlexicalchaining
AT rarti multidocumenttextsummarizationusingclusteringtechniquesandlexicalchaining