A survival modeling approach to biomedical search result diversification using wikipedia

Authors:
Xiaoshi Yin;Jimmy Xiangji Huang;Xiaofeng Zhou;Zhoujun Li
Affiliations:
York University and Beihang University , Toronto , ON, Canada;York University , Toronto, ON, Canada;York University , Toronto , ON, Canada;Beihang University , Beijing, China
Venue:
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Year:
2010

Citing 2
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Abstract

In this paper, we propose a probabilistic survival model derived from the survival analysis theory for measuring aspect novelty. The retrieved documents' query-relevance and novelty are combined at the aspect level for re-ranking. Experiments conducted on the TREC 2006 and 2007 Genomics collections demonstrate the effectiveness of the proposed approach in promoting ranking diversity for biomedical information retrieval.