Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11889/6360
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Quaroush, Aziz | en_US |
dc.contributor.author | Abu Farha, Ibrahim | en_US |
dc.contributor.author | Ghanem, Wasel | en_US |
dc.contributor.author | Washaha, Mahdi | en_US |
dc.contributor.author | Maali, Eman | en_US |
dc.date.accessioned | 2020-04-21T09:02:17Z | - |
dc.date.available | 2020-04-21T09:02:17Z | - |
dc.date.issued | 2019-03-26 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11889/6360 | - |
dc.description | Article to be published in : Journal of King Saud University – Computer and Information Sciences | en_US |
dc.description.abstract | The exponential growth of online textual data triggered the crucial need for an effective and powerful tool that automatically provides the desired content in a summarized form while preserving core information. In this paper, we propose an automatic, generic, and extractive Arabic single document summarizing method aiming at producing a sufficiently informative summary. The proposed extractive method evaluates each sentence based on a combination of statistical and semantic features in which a novel for-mulation is used taking into account sentence importance, coverage and diversity. Further, two summa-rizing techniques including score-based and supervised machine learning were employed to produce thesummary and then assist leveraging the designed features. We demonstrate the effectiveness of the pro-posed method through a set of experiments under EASC corpus using ROUGE measure. Compared tosome existing related work, the experimental evaluation shows the strength of the proposed methodin terms of precision, recall, and F-score performance metrics. | en_US |
dc.publisher | Science Direct | en_US |
dc.relation.ispartof | Journal of King Saud University | en_US |
dc.subject | Arabic language - Computer-assisted instruction | en_US |
dc.subject | Machine learning - Technique | en_US |
dc.subject | Cryptography | en_US |
dc.subject | Semantics | en_US |
dc.subject | Arabic language - Data processing | en_US |
dc.subject | Arabic language - Programmed instruction | en_US |
dc.title | An efficient single document Arabic text summarization using a combination of statistical and semantic features | en_US |
dc.type | Article | en_US |
dcterms.creator | Wasel Ghanem | en_US |
newfileds.department | Engineering and Technology | en_US |
newfileds.item-access-type | open_access | en_US |
newfileds.thesis-prog | none | en_US |
newfileds.general-subject | Computers and Information Technology | الحاسوب وتكنولوجيا المعلومات | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | Fulltext Publications |
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File | Description | Size | Format | |
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1-s2.0-S1319157818310498-main.pdf | 4.8 MB | Adobe PDF | View/Open |
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