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dc.contributor.authorÖzcan, Rıfaten_US
dc.contributor.authorAltıngövde, I. Ş.en_US
dc.contributor.authorUlusoy, Özgüren_US
dc.coverage.spatialBarcelona, Spainen_US
dc.date.accessioned2016-02-08T12:14:35Z
dc.date.available2016-02-08T12:14:35Z
dc.date.issued2012en_US
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/28222
dc.descriptionDate of Conference: 1-5 April 2012en_US
dc.descriptionConference name: 34th European Conference on IR Research, ECIR 2012en_US
dc.description.abstractA large number of Web information extraction algorithms are based on machine learning techniques. For such extraction algorithms, we propose employing a lazy learning strategy to build a specialized model for each test instance to improve the extraction accuracy and avoid the disadvantages of constructing a single general model. © 2012 Springer-Verlag Berlin Heidelberg.en_US
dc.language.isoEnglishen_US
dc.source.titleAdvances in Information Retrieval, 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012en_US
dc.relation.ispartofseriesLecture Notes in Computer Science;7224en_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-642-28997-2_65en_US
dc.subjectExtraction accuracyen_US
dc.subjectExtraction algorithmsen_US
dc.subjectGeneral modelen_US
dc.subjectLazy learningen_US
dc.subjectOn-machinesen_US
dc.subjectTest instancesen_US
dc.subjectWeb information extractionen_US
dc.subjectAlgorithmsen_US
dc.subjectInformation retrievalen_US
dc.titleIn praise of laziness: A lazy strategy for web information extractionen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage565en_US
dc.citation.epage568en_US
dc.citation.volumeNumber7224en_US
dc.identifier.doi10.1007/978-3-642-28997-2_65en_US


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