Yin, XS; Huang, JXJ; Li, ZJ. 2011. Mining and modeling linkage information from citation context for improving biomedical literature retrieval. INFORMATION PROCESSING & MANAGEMENT 47 (1): 53-67

[Eugene Garfield]

Yin, XS; Huang, JXJ; Li, ZJ. 2011. Mining and modeling linkage information from 
citation context for improving biomedical literature retrieval. INFORMATION 
PROCESSING & MANAGEMENT 47 (1): 53-67..

Author Full Name(s): Yin, Xiaoshi; Huang, Jimmy Xiangji; Li, Zhoujun
Language: English
Document Type: Article
Author Keywords: Probabilistic model; Citation analysis; Ranking; Biomedical 
information retrieval

Abstract: Mining linkage information from the citation graph has been shown to 
be effective in identifying important literatures. However, the question of how 
to utilize linkage information from the citation graph to facilitate literature 
retrieval still remains largely unanswered. In this paper, given the context of 
biomedical literature retrieval, we first conduct a case study in order to find out 
whether applying PageRank and HITS algorithms directly to the citation graph is 
the best way of utilizing citation linkage information for improving biomedical 
literature retrieval. Second, we propose a probabilistic combination framework 
for integrating citation information into the content-based information retrieval 
weighting model. Based on the observations of the case study, we present two 
strategies for modeling the linkage information contained in the citation graph. 
The proposed framework provides a theoretical support for the combination of 
content and linkage information. Under this framework, exhaustive parameter 
tuning can be avoided. Extensive experiments on three TREC Genomics 
collections demonstrate the advantages and effectiveness of our proposed 
methods. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights 
reserved.

Addresses: [Yin, Xiaoshi; Huang, Jimmy Xiangji] York Univ, Sch Informat 
Technol, Toronto, ON M3J 2R7, Canada; [Yin, Xiaoshi; Li, Zhoujun] Beihang 
Univ, Sch Comp Sci & Engn, Beijing, Peoples R China

Reprint Address: Huang, JXJ, York Univ, Sch Informat Technol, Toronto, ON M3J 
2R7, Canada.

E-mail Address: xiaoshiyin at cse.buaa.edu.cn; jhuang at yorku.ca; 
lizj at buaa.edu.cn
ISSN: 0306-4573
DOI: 10.1016/j.ipm.2010.03.010
URL (not open access): http://portal.acm.org/citation.cfm?
id=1872512&CFID=6292156&CFTOKEN=46900972