We present a novel approach to  fusing  document lists that are retrieved in response to a query. Our approach is based on utilizing information induced from  inter-document similarities  . Specifically, the key insight guiding the derivation of our methods is that similar documents from different lists can provide  relevance-status  support to each other. We use a graph-based method to model relevance-status propagation between documents. The propagation is governed by inter-document-similarities and by retrieval scores of documents in the lists. Empirical evaluation shows the effectiveness of our methods in fusing TREC  runs  .
['Anna Khudyak Kozorovitzky', 'Oren Kurland']
From Identical to Similar: Fusing Retrieved Lists Based on Inter-document Similarities