A framework for mining interesting pattern sets

Bie, T; Kontonasios, K; Spyropoulou, E

dc.contributor.author	Bie, T	en
dc.contributor.author	Kontonasios, K	en
dc.contributor.author	Spyropoulou, E	en
dc.date.accessioned	2014-03-01T02:00:50Z
dc.date.available	2014-03-01T02:00:50Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/29143
dc.subject	Coding Theory	en
dc.subject	Empirical Evaluation	en
dc.subject	Interestingness Measure	en
dc.subject	Maximum Entropy	en
dc.subject	Prior Information	en
dc.title	A framework for mining interesting pattern sets	en
heal.type	journalArticle	en
heal.identifier.primary	10.1145/1964897.1964920	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1964897.1964920	en
heal.publicationDate	2011	en
heal.abstract	This paper suggests a framework for mining subjectively interesting pattern sets that is based on two components: (1) the encoding of prior information in a model for the data miner's state of mind; (2) the search for a pattern set that is maximally informative while efficient to convey to the data miner. We illustrate the framework with an instantiation for	en
heal.journalName	Sigkdd Explorations	en
dc.identifier.doi	10.1145/1964897.1964920	en