Huang S, Xue GR, Zhang BY, Chen Z, Yu Y, Ma WY " TSSP: A reinforcement algorithm to find related papers" IEEE/WIC/ACM International Conference On Web Intelligence (WI 2004), Proceedings : 117-123, 2004

[Eugene Garfield]

Shen Huang : Shuang at cs.sjtu.edu.cn
Gui-Rong Xue : grxue at sjtu.edu.cn
Yong Yu : yyu at cs.sjtu.edu.cn
Ben-Yu Zhang : byzhang at microsoft.com
Zheng Chen : zhengc at microsoft.com
Wei-Ying Ma : wyma at microsoft.com


Title: TSSP: A reinforcement algorithm to find related papers

Author(s): Huang S, Xue GR, Zhang BY, Chen Z, Yu Y, Ma WY

Source: IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI
2004), PROCEEDINGS : 117-123, 2004

Editor(s): Zhong N, Tirri H, Yao YY, Zhou L, Liu J, Cercone N

Document Type: Article
Language: English
Cited References: 21

Conference Information: IEEE/WIC/ACM International Conference on Web
Intelligence
Beijing, PEOPLES R CHINA, SEP 20-24, 2004

IEEE Comp Soc; AMC; Web Intelligence Consortium; Beijing Univ Technol; NSFC

Abstract:
content analysis and citation analysis are two common methods it?
recommending system. Compared with content analysis, citation analysis can
discover more implicitly related papers. However, the citation-based
methods may introduce more noise in citation graph and cause topic drift.
Some work combine content with citation to improve similarity measurement.
The problem is that the two features are not used to reinforce each other
to get better result. To solve the problem, we propose a new algorithm,
Topic Sensitive Similarity Propagation (TSSP), to effectively integrate
content similarity, into similarity propagation. TSSP has two parts.
citation context based propagation and iterative reinforcement. First,
citation contexts provide clues for which papers are topic related to and
filter out less irrelevant citations. Second, iteratively integrating
content and citation similarity enable them to reinforce each other during
the propagation. The experimental results of a user study show TSSP
outperforms other algorithms in almost all cases.

KeyWords Plus: RETRIEVAL; INFORMATION

Addresses: Huang S (reprint author), Shanghai Jiao Tong Univ, Shanghai
200030, Peoples R China
Shanghai Jiao Tong Univ, Shanghai 200030, Peoples R China

Publisher: IEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS
ALAMITOS, CA 90720-1264 USA
IDS Number: BBB14

ISBN: 0-7695-2100-2

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