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Experiments on Incremental Clustering

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dc.contributor.author Can, Fazli en_US
dc.date.accessioned 2008-07-22T19:31:03Z en_US
dc.date.accessioned 2013-07-10T15:06:36Z
dc.date.available 2008-07-22T19:31:03Z en_US
dc.date.available 2013-07-10T15:06:36Z
dc.date.issued 1991-08-01 en_US
dc.date.submitted 2008-03-17 en_US
dc.identifier.uri
dc.identifier.uri http://hdl.handle.net/2374.MIA/187 en_US
dc.description.abstract Clustering of very large document databases is essential to reduce the spacehime complexity of information retrieval. The periodic updating of clusters is required due to the dynamic nature of databases. An algorithm for incremental clustering at discrete times is introduced, Its complexity and cost analysis and an investigation of the expected behavior of the algorithm are provided. Through empirical testing, it is shown that the algorithm is achieving its purpose in terms of being cost effective, generating statistically valid clusters that are compatible with those of reclustering, and providing effective information retrieval. en_US
dc.title Experiments on Incremental Clustering en_US
dc.type Text en_US
dc.type.genre Report en_US


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