Similar document retrieval is the problem of finding documents that are most similar to a given query document. In this work, we present a retrieval based on clustering of the documents that approximates the nearest neighbor search. It is done by determining the clusters that are most similar to the query document and restricting the search to the documents in these clusters. Cluster representation has an important role in the effectiveness of the search procedure, since the inclusion of a cluster in the restricted search space depends on whether its representation matches the query document. We analyse three cluster representations and their role in the performance of the proposed search procedure.
similar document retrieval, text clustering, nearest neighbor search
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