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dc.contributor.authorBozkurt, İlker Nadien_US
dc.contributor.authorBağlıoğlu, Özgüren_US
dc.contributor.authorUyar, Erkanen_US
dc.coverage.spatialAnkara, Turkey
dc.date.accessioned2016-02-08T11:41:59Z
dc.date.available2016-02-08T11:41:59Z
dc.date.issued2007-11en_US
dc.identifier.urihttp://hdl.handle.net/11693/27016
dc.descriptionDate of Conference: 7-9 Nov. 2007
dc.descriptionConference name: 22nd international symposium on computer and information sciences, 2007
dc.description.abstractAuthorship attribution is the process of determining the writer of a document. In literature, there are lots of classification techniques conducted in this process. In this paper we explore information retrieval methods such as tf-idf structure with support vector machines, parametric and nonparametric methods with supervised and unsupervised (clustering) classification techniques in authorship attribution. We performed various experiments with articles gathered from Turkish newspaper Milliyet. We performed experiments on different features extracted from these texts with different classifiers, and combined these results to improve our success rates. We identified which classifiers give satisfactory results on which feature sets. According to experiments, the success rates dramatically changes with different combinations, however the best among them are support vector classifier with bag of words, and Gaussian with function words. ©2007 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.title22nd International Symposium on Computer and Information Sciences, ISCIS 2007 - Proceedingsen_US
dc.relation.isversionofhttps://doi.org/10.1109/ISCIS.2007.4456854en_US
dc.subjectAuthorship attributionen_US
dc.subjectClassifier feature reationshipen_US
dc.subjectFeature reductionen_US
dc.subjectParametric nonparametric calssifiersen_US
dc.subjectText categorizationen_US
dc.subjectClassifiersen_US
dc.subjectCommunicationen_US
dc.subjectCyberneticsen_US
dc.subjectExperimentsen_US
dc.subjectImage retrievalen_US
dc.subjectInformation managementen_US
dc.subjectInformation retrievalen_US
dc.subjectInformation scienceen_US
dc.subjectInformation servicesen_US
dc.subjectLearning systemsen_US
dc.subjectSearch enginesen_US
dc.subjectSupport vector machinesen_US
dc.subjectVectorsen_US
dc.subjectAuthorship attributionen_US
dc.subjectBag of wordsen_US
dc.subjectClassification methodsen_US
dc.subjectClassification techniquesen_US
dc.subjectFeature setsen_US
dc.subjectFunction wordsen_US
dc.subjectGaussianen_US
dc.subjectInternational symposiumen_US
dc.subjectNon parametric methodsen_US
dc.subjectRetrieval methodsen_US
dc.subjectSupport vector classifier (SVC)en_US
dc.subjectTurkishen_US
dc.subjectVector machinesen_US
dc.subjectClassification (of information)en_US
dc.titleAuthorship attribution: performance of various features and classification methodsen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage158en_US
dc.citation.epage162en_US
dc.identifier.doi10.1109/ISCIS.2007.4456854en_US
dc.publisherIEEE


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