Integrated query answering with weighted fuzzy rules

Chortaras, A; Stamou, G; Stafylopatis, A

dc.contributor.author	Chortaras, A	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:44:42Z
dc.date.available	2014-03-01T02:44:42Z
dc.date.issued	2007	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31940
dc.subject	Database Query	en
dc.subject	Fuzzy Logic Programming	en
dc.subject	Fuzzy Rules	en
dc.subject	Machine Learning	en
dc.subject	Query Answering	en
dc.subject	Relational Database System	en
dc.subject	Neural Network	en
dc.subject.other	Integration	en
dc.subject.other	Logic programming	en
dc.subject.other	Query processing	en
dc.subject.other	Relational database systems	en
dc.subject.other	Set theory	en
dc.subject.other	Fuzzy facts	en
dc.subject.other	Fuzzy logic programs	en
dc.subject.other	Prototype systems	en
dc.subject.other	Query answering services	en
dc.subject.other	Fuzzy rules	en
dc.title	Integrated query answering with weighted fuzzy rules	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-75256-1_67	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-75256-1_67	en
heal.publicationDate	2007	en
heal.abstract	Weighted fuzzy logic programs increase the expressivity of fuzzy logic programs by allowing the association of a significance weight with each atom in the body of a fuzzy rule. In this paper, we propose a prototype system for the practical integration of weighted fuzzy logic programs with relational database systems in order to provide efficient query answering services. In the system, a dynamic weighted fuzzy logic program is a set of rules together with a set of database queries, fuzzification transformations and fact derivation rules, which allow the provided set of rules to be augmented with a set of fuzzy facts retrieved from the underlying databases. The weights of the rules may be estimated by a neural network-based machine learning process using some specially designated for this purpose training database data. © Springer-Verlag Berlin Heidelberg 2007.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-75256-1_67	en
dc.identifier.volume	4724 LNAI	en
dc.identifier.spage	767	en
dc.identifier.epage	778	en