Modeling interestingness of streaming classification rules as a classification problem

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dc.citation.epage176en_US
dc.citation.spage168en_US
dc.contributor.authorAydın, Tolgaen_US
dc.contributor.authorGüvenir, Halil Altayen_US
dc.coverage.spatialIzmir, Turkey
dc.date.accessioned2016-02-08T11:48:48Z
dc.date.available2016-02-08T11:48:48Z
dc.date.issued2005-06en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 16-17 June, 2005
dc.descriptionConference name: Turkish Symposium on Artificial Intelligence and Neural Networks. TAINN 2005: Artificial Intelligence and Neural Networks
dc.description.abstractInducing classification rules on domains from which information is gathered at regular periods lead the number of such classification rules to be generally so huge that selection of interesting ones among all discovered rules becomes an important task. At each period, using the newly gathered information from the domain, the new classification rules are induced. Therefore, these rules stream through time and are so called streaming classification rules. In this paper, an interactive classification rules' interestingness learning algorithm (ICRIL) is developed to automatically label the classification rules either as "interesting" or "uninteresting" with limited user interaction. In our study, VFFP (Voting Fuzzified Feature Projections), a feature projection based incremental classification algorithm, is also developed in the framework of ICRIL. The concept description learned by the VFFP is the interestingness concept of streaming classification rules. © Springer-Verlag Berlin Heidelberg 2006.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:48:48Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2006en
dc.identifier.doi10.1007/11803089_20en_US
dc.identifier.urihttp://hdl.handle.net/11693/27255
dc.language.isoEnglishen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/11803089_20en_US
dc.source.titleTurkish Symposium on Artificial Intelligence and Neural Networks TAINN, 2005en_US
dc.subjectClassification (of information)en_US
dc.subjectData processingen_US
dc.subjectLearning algorithmsen_US
dc.subjectLogic programmingen_US
dc.subjectUser interfacesen_US
dc.subjectIncremental classification algorithmsen_US
dc.subjectInterestingness learning algorithm (ICRIL)en_US
dc.subjectStreaming classificationen_US
dc.subjectProblem solvingen_US
dc.titleModeling interestingness of streaming classification rules as a classification problemen_US
dc.typeConference Paperen_US

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