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Methods for fusing document lists that were retrieved in response to a queryoften utilize the retrieval scores and/or ranks of documents in the lists. Wepresent a novel fusion approach that is based on using, in addition,information induced from inter-document similarities. Specifically, our methodslet similar documents from different lists provide relevance-status support toeach other. We use a graph-based method to model relevance-status propagationbetween documents. The propagation is governed by inter-document-similaritiesand by retrieval scores of documents in the lists. Empirical evaluationdemonstrates the effectiveness of our methods in fusing TREC runs. Theperformance of our most effective methods transcends that of effective fusionmethods that utilize only retrieval scores or ranks.

From "Identical" to "Similar": Fusing Retrieved Lists Based on Inter-Document Similarities