Document re-ranking by generality in bio-medical information retrieval.

Yan, Xin; Li, Xue; Song, Dawei

Abstract

Document ranking is an important process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. Traditional document ranking methods are mostly based on the similarity computations between documents and query. In this paper we argue that the similarity-based document ranking is insufficient in some cases. There are two reasons. Firstly it is about the increased information variety. There are far too many different types documents available now for user to search. The second is about the users variety. In many cases user may want to retrieve documents that are not only similar but also general or broad regarding a certain topic. This is particularly the case in some domains such as bio-medical IR. In this paper we propose a novel approach to re-rank the retrieved documents by incorporating the similarity with their generality. By an ontology-based analysis on the semantic cohesion of text, document generality can be quantified. The retrieved documents are then re-ranked by their combined scores of similarity and the closeness of documents' generality to the query's. Our experiments have shown an encouraging performance on a large bio-medical document collection, OHSUMED, containing 348,566 medical journal references and 101 test queries.

Citation

YAN, X., LI, X. and SONG, D. 2005. Document re-ranking by generality in bio-medical information retrieval. In Ngu, A.H.H., Kitsuregawa, M., Neuhold, E.J., Chung, J.-Y. and Sheng, Q.Z. (eds.) Web information systems engineering: proceedings of the 6th International conference on web information systems engineering (WISE 2005), 20-22 November 2005, New York, USA. Lecture notes in computer science, 3806. Berlin: Springer [online], pages 376-389. Available from: https://doi.org/10.1007/11581062_28

• Conference Name: 6th International conference on web information systems engineering (WISE 2005)
• Conference Location: New York, USA
• Start Date: Nov 20, 2005
• End Date: Nov 22, 2005
• Acceptance Date: Dec 31, 2005
• Online Publication Date: Dec 31, 2005
• Publication Date: Dec 31, 2005
• Deposit Date: May 29, 2009
• Publicly Available Date: May 29, 2009
• Publisher: Springer
• Pages: 376-389
• Series Title: Lecture notes in computer science
• Series Number: 3806
• ISBN: 3540300171; 9783540300175
• DOI: https://doi.org/10.1007/11581062_28
• Keywords: Document ranking; Information retrieval; Biomedical
• Public URL: http://hdl.handle.net/10059/351