AUTOMATIC ABSTRACTING IMPORTANT SENTENCES
F. J. Ren ()
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F. J. Ren: Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima, Tokushima, Japan, 770-8506, Japan
International Journal of Information Technology & Decision Making (IJITDM), 2005, vol. 04, issue 01, 141-152
Abstract:
Being increasingly popular, the Internet greatly changes our lives. We can conveniently receive and send information via the Internet. With the information explosion on the Web, it is becoming crucial to develop means to automatically extract important sentences from the Web articles. In this paper, we propose a method which uses both statistical and structural information for sentence extraction. In addition, following the analysis of human's extractions, several heuristic rules are added to filter out non-important sentences and to prevent similar sentences from being extracted. Our experimental results proved the effectiveness of these means. In particular, once the heuristic rules being added, a significant improvement has been observed.
Keywords: Automatic Extraction of Important Sentence; statistical information; structural feature; web (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:04:y:2005:i:01:n:s0219622005001428
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DOI: 10.1142/S0219622005001428
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