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Document Similarity Self-Join with MapReduce
2010
2010 IEEE International Conference on Data Mining
Given a collection of objects, the Similarity Self-Join problem requires to discover all those pairs of objects whose similarity is above a user defined threshold. In this paper we focus on document collections, which are characterized by a sparseness that allows effective pruning strategies. Our contribution is a new parallel algorithm within the MapReduce framework. This work borrows from the state of the art in serial algorithms for similarity join and MapReducebased techniques for
doi:10.1109/icdm.2010.70
dblp:conf/icdm/BaragliaML10
fatcat:ueq5jsum4bewthlveisuwjybna