Modelling knowledge summarization by evolving fuzzy grammar
Summarized text is a simplified and condensed version of the original text containing highlighted information to help the audience get the gist in a short period of time. Typically, text summarization produces abstract or a paragraph-like outputs by omitting details and irrelevant information. Howev...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Science Publications
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30611/ http://psasir.upm.edu.my/id/eprint/30611/1/ajassp.2013.606.614.pdf |
| _version_ | 1848846727241531392 |
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| author | Mohd Sharef, Nurfadhlina Abdul Halin, Alfian Mustapha, Norwati |
| author_facet | Mohd Sharef, Nurfadhlina Abdul Halin, Alfian Mustapha, Norwati |
| author_sort | Mohd Sharef, Nurfadhlina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Summarized text is a simplified and condensed version of the original text containing highlighted information to help the audience get the gist in a short period of time. Typically, text summarization produces abstract or a paragraph-like outputs by omitting details and irrelevant information. However,the text summary can also be produced in a visualized form, such as a chart, graph or table representing a collection of similar cases. The visualized version generates a statistical-like presentation, which often involves numerical and ordinal observation of the gathered knowledge from the text. This requires lexical
syntactic understanding of the text. Essential to achieve this goal is topic identification, message analysis/ interpretation and knowledge summarization generation. The objective of this study is to model knowledge summarization problem using the evolving fuzzy grammar technique and we focus on metadata generation for producing visualized knowledge summarization. The process comprises of: (i) identifying the underlying structure of the texts for knowledge summarization, (ii) represent the identified knowledge for summarization manipulation and (iii) presentation of the summarized knowledge. A prototype called FTCat©is developed as a proof of concept and we demonstrate its practicality in summarizing news reports. |
| first_indexed | 2025-11-15T09:07:18Z |
| format | Article |
| id | upm-30611 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:07:18Z |
| publishDate | 2013 |
| publisher | Science Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-306112017-11-29T03:14:52Z http://psasir.upm.edu.my/id/eprint/30611/ Modelling knowledge summarization by evolving fuzzy grammar Mohd Sharef, Nurfadhlina Abdul Halin, Alfian Mustapha, Norwati Summarized text is a simplified and condensed version of the original text containing highlighted information to help the audience get the gist in a short period of time. Typically, text summarization produces abstract or a paragraph-like outputs by omitting details and irrelevant information. However,the text summary can also be produced in a visualized form, such as a chart, graph or table representing a collection of similar cases. The visualized version generates a statistical-like presentation, which often involves numerical and ordinal observation of the gathered knowledge from the text. This requires lexical syntactic understanding of the text. Essential to achieve this goal is topic identification, message analysis/ interpretation and knowledge summarization generation. The objective of this study is to model knowledge summarization problem using the evolving fuzzy grammar technique and we focus on metadata generation for producing visualized knowledge summarization. The process comprises of: (i) identifying the underlying structure of the texts for knowledge summarization, (ii) represent the identified knowledge for summarization manipulation and (iii) presentation of the summarized knowledge. A prototype called FTCat©is developed as a proof of concept and we demonstrate its practicality in summarizing news reports. Science Publications 2013-06-10 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30611/1/ajassp.2013.606.614.pdf Mohd Sharef, Nurfadhlina and Abdul Halin, Alfian and Mustapha, Norwati (2013) Modelling knowledge summarization by evolving fuzzy grammar. American Journal of Applied Sciences, 10 (6). pp. 606-614. ISSN 1546-9239; ESSN: 1554-3641 http://thescipub.com/abstract/10.3844/ajassp.2013.606.614 10.3844/ajassp.2013.606.614 |
| spellingShingle | Mohd Sharef, Nurfadhlina Abdul Halin, Alfian Mustapha, Norwati Modelling knowledge summarization by evolving fuzzy grammar |
| title | Modelling knowledge summarization by evolving fuzzy grammar |
| title_full | Modelling knowledge summarization by evolving fuzzy grammar |
| title_fullStr | Modelling knowledge summarization by evolving fuzzy grammar |
| title_full_unstemmed | Modelling knowledge summarization by evolving fuzzy grammar |
| title_short | Modelling knowledge summarization by evolving fuzzy grammar |
| title_sort | modelling knowledge summarization by evolving fuzzy grammar |
| url | http://psasir.upm.edu.my/id/eprint/30611/ http://psasir.upm.edu.my/id/eprint/30611/ http://psasir.upm.edu.my/id/eprint/30611/ http://psasir.upm.edu.my/id/eprint/30611/1/ajassp.2013.606.614.pdf |