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dc.contributor.authorLiu, Heng-Hui Jr
dc.contributor.authorHuang, Yi-Ting Jr
dc.contributor.authorChiang, Jung-Hsien Jr
dc.date.accessioned2011-02-18T03:16:30Z
dc.date.accessioned2020-05-18T03:10:42Z-
dc.date.available2011-02-18T03:16:30Z
dc.date.available2020-05-18T03:10:42Z-
dc.date.issued2011-02-18T03:16:30Z
dc.date.submitted2010-12-18
dc.identifier.urihttp://dspace.lib.fcu.edu.tw/handle/2377/29990-
dc.description.abstractWith the growing availability of full-text scientific articles, how text mining researchers utilize them has become an important issue. Although abstract and title provide accurate and summary information of article, lots of details are inevitably lost for its short space. The primary goal of the study is to utilize the advantages of abstract and full-text to ease the burden of reading. Finding essential information from abstract, using this to search and to rank paragraphs in full-text, the proposed approach recommends significant paragraphs to user for saving time of perusing whole article. Finally we evaluated the performance of our system, it outperformed the baseline approach both in human ratings and ROUGE scores.
dc.description.sponsorshipNational Cheng Kung University,Tainan
dc.format.extent6p.
dc.relation.ispartofseries2010 ICS會議
dc.subjecttext mining
dc.subjectsummarization
dc.subjectranking
dc.subjectfull text
dc.subject.otherBiomedical Informatics
dc.titleA Study on Paragraph Ranking and Recommendation by Topic Information Retrieval from Biomedical Literature
分類:2010年 ICS 國際計算機會議(如需查看全文,請連結至IEEE Xplore網站)

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