A taxonomy fuzzy filtering approach

Vrettos, S; Stafylopatis, A

dc.contributor.author	Vrettos, S	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T01:52:27Z
dc.date.available	2014-03-01T01:52:27Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/26623
dc.subject	Bayes Classifier	en
dc.subject	Fuzzy Logic	en
dc.subject	Indexing Terms	en
dc.subject	Support Vector Machine	en
dc.subject	Open Directory Project	en
dc.title	A taxonomy fuzzy filtering approach	en
heal.type	journalArticle	en
heal.identifier.primary	10.2298/JAC0301026V	en
heal.identifier.secondary	http://dx.doi.org/10.2298/JAC0301026V	en
heal.publicationDate	2003	en
heal.abstract	Our work proposes the use of topic taxonomies as part of a filtering language. Given a taxonomy, a classifier is trained for each one of its topics. The user is able to formulate logical rules combining the available topics, e.g. (Topic1 AND Topic2) OR Topic3, in order to filter related documents in a stream. Using the trained classifiers, every document	en
heal.journalName	Journal of Automatic Control	en
dc.identifier.doi	10.2298/JAC0301026V	en