Promoting ranking diversity for biomedical information retrieval using wikipedia

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Abstract

In this paper, we propose a cost-based re-ranking method to promote ranking diversity for biomedical information retrieval. The proposed method concerns with finding passages that cover many different aspects of a query topic. First, aspects covered by retrieved passages are detected and explicitly presented by Wikipedia concepts. Then, an aspect filter based on a two-stage model is introduced. It ranks the detected aspects in decreasing order of the probability that an aspect is generated by the query. Finally, retrieved passages are re-ranked using the proposed cost-based re-ranking method which ranks a passage according to the number of new aspects covered by the passage and the query-relevance of aspects covered by the passage. A series of experiments conducted on the TREC 2006 and 2007 Genomics collections demonstrate the effectiveness of the proposed method in promoting ranking diversity for biomedical information retrieval. © 2010 Springer-Verlag Berlin Heidelberg.

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Yin, X., Huang, X., & Li, Z. (2010). Promoting ranking diversity for biomedical information retrieval using wikipedia. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 495–507). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_43

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