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oaioai:docs.lib.purdue.edu:open_access_dissertations-2594

GENERIC FRAMEWORKS FOR INTERACTIVE PERSONALIZED INTERESTING PATTERN DISCOVERY

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Publication date
1 January 2016
Publisher
'Purdue University (bepress)'

Abstract

The traditional frequent pattern mining algorithms generate an exponentially large number of patterns of which a substantial portion are not much significant for many data analysis endeavours. Due to this, the discovery of a small number of interesting patterns from the exponentially large number of frequent patterns according to a particular user\u27s interest is an important task. Existing works on patter

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This paper was published in Purdue E-Pubs.

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