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This paper proposes a novel document re-ranking approach in information retrieval, which is done by a label propagationbased semi-supervised learning algorithm to utilize the intrinsic structure underlying in the large document data. Since no labeled relevant or irrelevant documents are generally available in IR, our approach tries to extract some pseudo labeled documents from the ranking list of the initial retrieval. For pseudo relevant documents, we determine a cluster of documents from thedoi:10.1145/1183614.1183713 dblp:conf/cikm/YangJZNX06 fatcat:checcs6atrgulfrh23lxt4hz6m