Automatic Text Summarization for Oil and Gas Topic
Information sharing and gathering are important in the rapid advancement era of technology. The existence of WWW has caused rapid growth of information explosion. Readers are overloaded with too many lengthy text documents in which they are more interested in shorter versions. Oil and gas industry c...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/2017/ http://scholars.utp.edu.my/id/eprint/2017/1/v42-6.pdf |
| _version_ | 1848659194314489856 |
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| author | Chen, Y.Y. Foong, Oi Mean Yong, S.P. Kurniawan, Iwan |
| author_facet | Chen, Y.Y. Foong, Oi Mean Yong, S.P. Kurniawan, Iwan |
| author_sort | Chen, Y.Y. |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | Information sharing and gathering are important in the rapid advancement era of technology. The existence of WWW has caused rapid growth of information explosion. Readers are overloaded with too many lengthy text documents in which they are more interested in shorter versions. Oil and gas industry could not escape from this predicament. In this paper, we develop an Automated Text Summarization System known as AutoTextSumm to extract the salient points of oil and gas drilling articles by incorporating statistical approach, keywords identification, synonym words and sentence’s position. In this study, we have conducted interviews with Petroleum Engineering experts and English Language experts to identify the list of most commonly used keywords in the oil and gas drilling domain. The system performance of AutoTextSumm is evaluated using the formulae of precision, recall and F-score. Based on the experimental results, AutoTextSumm has produced satisfactory performance with F-score of 0.81. |
| first_indexed | 2025-11-13T07:26:33Z |
| format | Conference or Workshop Item |
| id | oai:scholars.utp.edu.my:2017 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:26:33Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:20172017-03-20T01:57:02Z http://scholars.utp.edu.my/id/eprint/2017/ Automatic Text Summarization for Oil and Gas Topic Chen, Y.Y. Foong, Oi Mean Yong, S.P. Kurniawan, Iwan QA75 Electronic computers. Computer science Information sharing and gathering are important in the rapid advancement era of technology. The existence of WWW has caused rapid growth of information explosion. Readers are overloaded with too many lengthy text documents in which they are more interested in shorter versions. Oil and gas industry could not escape from this predicament. In this paper, we develop an Automated Text Summarization System known as AutoTextSumm to extract the salient points of oil and gas drilling articles by incorporating statistical approach, keywords identification, synonym words and sentence’s position. In this study, we have conducted interviews with Petroleum Engineering experts and English Language experts to identify the list of most commonly used keywords in the oil and gas drilling domain. The system performance of AutoTextSumm is evaluated using the formulae of precision, recall and F-score. Based on the experimental results, AutoTextSumm has produced satisfactory performance with F-score of 0.81. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/2017/1/v42-6.pdf Chen, Y.Y. and Foong, Oi Mean and Yong, S.P. and Kurniawan, Iwan (2008) Automatic Text Summarization for Oil and Gas Topic. In: World Academy of Science, Engineering and Technology (WASET) , 30 August 2008. http://www.waset.ac.nz/journals/waset/v42/v42-6.pdf |
| spellingShingle | QA75 Electronic computers. Computer science Chen, Y.Y. Foong, Oi Mean Yong, S.P. Kurniawan, Iwan Automatic Text Summarization for Oil and Gas Topic |
| title | Automatic Text Summarization for Oil and Gas Topic |
| title_full | Automatic Text Summarization for Oil and Gas Topic |
| title_fullStr | Automatic Text Summarization for Oil and Gas Topic |
| title_full_unstemmed | Automatic Text Summarization for Oil and Gas Topic |
| title_short | Automatic Text Summarization for Oil and Gas Topic |
| title_sort | automatic text summarization for oil and gas topic |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/2017/ http://scholars.utp.edu.my/id/eprint/2017/ http://scholars.utp.edu.my/id/eprint/2017/1/v42-6.pdf |