Kurland, O; Lee, L. 2010. PageRank without Hyperlinks: Structural Reranking using Links Induced by Language Models. ACM TRANSACTIONS ON INFORMATION SYSTEMS 28 (4): art. no.-18

[Eugene Garfield]

Kurland, O; Lee, L. 2010. PageRank without Hyperlinks: Structural Reranking 
using Links Induced by Language Models. ACM TRANSACTIONS ON 
INFORMATION SYSTEMS 28 (4): art. no.-18..

Author Full Name(s): Kurland, Oren; Lee, Lillian
Language: English
Document Type: Article

Author Keywords: Algorithms; Experimentation; Language modeling; PageRank; 
HITS; hubs; authorities; social networks; high-accuracy retrieval; graph-based 
retrieval; structural reranking
KeyWords Plus: INFORMATION-RETRIEVAL; CLASSIFICATION

Abstract: The ad hoc retrieval task is to find documents in a corpus that are 
relevant to a query. Inspired by the PageRank and HITS (hubs and authorities) 
algorithms for Web search, we propose a structural reranking approach to ad-
hoc retrieval that applies to settings with no hyperlink information. We reorder 
the documents in an initially retrieved set by exploiting implicit asymmetric 
relationships among them. We consider generation links, which indicate that the 
language model induced from one document assigns high probability to the text 
of another. We study a number of reranking criteria based on measures of 
centrality in the graphs formed by generation links, and show that integrating 
centrality into standard language-model-based retrieval is quite effective at 
improving precision at top ranks; the best resultant performance is comparable, 
and often superior, to that of a state-of-the-art pseudo-feedback-based 
retrieval approach. In addition, we demonstrate the merits of our language-
model-based method for inducing interdocument links by comparing it to 
previously suggested notions of interdocument similarities (e.g., cosines within 
the vector-space model). We also show that our methods for inducing 
centrality are substantially more effective than approaches based on 
document-specific characteristics, several of which are novel to this study.

Addresses: [Kurland, Oren] Technion Israel Inst Technol, IL-32000 Haifa, Israel; 
[Lee, Lillian] Cornell Univ, Ithaca, NY 14853 USA

Reprint Address: Kurland, O, Technion Israel Inst Technol, IL-32000 Haifa, 
Israel.

E-mail Address: kurland at ie.technion.ac.il; llee at cs.cornell.edu
ISSN: 1046-8188
DOI: 10.1145/1852102.1852104
URL (not open access): http://portal.acm.org/citation.cfm?
id=1852104&CFID=6292156&CFTOKEN=46900972