A study on paragraph ranking and recommendation by topic information retrieval from biomedical literature

Heng Hui Liu, Yi Ting Huang, Jung-Hsien Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

With 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.

Original languageEnglish
Title of host publicationICS 2010 - International Computer Symposium
Pages859-864
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 1
Event2010 International Computer Symposium, ICS 2010 - Tainan, Taiwan
Duration: 2010 Dec 162010 Dec 18

Publication series

NameICS 2010 - International Computer Symposium

Other

Other2010 International Computer Symposium, ICS 2010
CountryTaiwan
CityTainan
Period10-12-1610-12-18

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Fingerprint Dive into the research topics of 'A study on paragraph ranking and recommendation by topic information retrieval from biomedical literature'. Together they form a unique fingerprint.

Cite this