Lin, J (Lin, Jimmy) PageRank without hyperlinks: Reranking with PubMed related article networks for biomedical text retrieval BMC BIOINFORMATICS, 9: Art. No. 270 JUN 6 2008

[Eugene Garfield]

E-mail Address: jimmylin at umd.edu 

Author(s): Lin, J (Lin, Jimmy) 

Title: PageRank without hyperlinks: Reranking with PubMed related article 
networks for biomedical text retrieval 

Source: BMC BIOINFORMATICS, 9: Art. No. 270 JUN 6 2008 

Language: English 

Document Type: Article 

Abstract: Background: Graph analysis algorithms such as PageRank and HITS 
have been successful in Web environments because they are able to extract 
important inter-document relationships from manually-created hyperlinks. 
We consider the application of these techniques to biomedical text 
retrieval. In the current PubMed (R) search interface, a MEDLINE (R) 
citation is connected to a number of related citations, which are in turn 
connected to other citations. Thus, a MEDLINE record represents a node in 
a vast content-similarity network. This article explores the hypothesis 
that these networks can be exploited for text retrieval, in the same 
manner as hyperlink graphs on the Web.
Results: We conducted a number of reranking experiments using the TREC 
2005 genomics track test collection in which scores extracted from 
PageRank and HITS analysis were combined with scores returned by an off-
the-shelf retrieval engine. Experiments demonstrate that incorporating 
PageRank scores yields significant improvements in terms of standard 
ranked-retrieval metrics.
Conclusion: The link structure of content-similarity networks can be 
exploited to improve the effectiveness of information retrieval systems. 
These results generalize the applicability of graph analysis algorithms to 
text retrieval in the biomedical domain. 

Addresses: Natl Lib Med, Natl Ctr Biotechnol Informat, Bethesda, MD 20894 
USA; Univ Maryland, The iSch, College Pk, MD 20742 USA 

Reprint Address: Lin, J, Natl Lib Med, Natl Ctr Biotechnol Informat, 
Bethesda, MD 20894 USA. 

E-mail Address: jimmylin at umd.edu 

Cited Reference Count: 25 

Times Cited: 0 

Publisher: BIOMED CENTRAL LTD 

Publisher Address: CURRENT SCIENCE GROUP, MIDDLESEX HOUSE, 34-42 CLEVELAND 
ST, LONDON W1T 4LB, ENGLAND 

ISSN: 1471-2105 

DOI: 10.1186/1471-2105-9-270 

29-char Source Abbrev.: BMC BIOINFORMATICS 

ISO Source Abbrev.: BMC Bioinformatics 

Source Item Page Count: 12 

Subject Category: Biochemical Research Methods; Biotechnology & Applied 
Microbiology; Mathematical & Computational Biology 

ISI Document Delivery No.: 326JC 

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