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dc.contributor.advisorTekir, Selma
dc.contributor.authorÇavuş, Engin-
dc.descriptionThesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2014en_US
dc.descriptionIncludes bibliographical references (leaves: 28-29)en_US
dc.descriptionText in English; Abstract: Turkish and Englishen_US
dc.descriptionvii, 32 leavesen_US
dc.description.abstractOver the past years the number of published news articles have an excessive increase. In the past, there was less channel of communication. Moreover the articles were classified by the human operators. In the course of time the means of the communication increased and expanded rapidly. The need for an automated news classification tool is inevitable. The text classification is a statistical machine learning procedure that individual text items are placed into groups based on quantitative information. In this study, an event based news classification and sequencing system is proposed, the model is explained. The decision making process is represented. A case study is prepared and analyzed.en_US
dc.publisherIzmir Institute of Technologyen_US
dc.subject.lcshMarkov processesen_US
dc.subject.lcshMultimedia systems--Computer programsen_US
dc.subject.lcshNatural language processing (Computer science)en_US
dc.titleAn event-based Hidden Makrov Model approach to news classification and sequencingen_US
dc.title.alternativeOlay tabanlı Gizli Markov Modeli yaklaşımı ile haber sınıflandırması ve sıralamasıen_US
dc.typeMaster Thesisen_US
dc.institutionauthorÇavuş, Engin-
dc.departmentIzmir Institute of Technology. Computer Engineeringen_US
item.openairetypeMaster Thesis-
item.fulltextWith Fulltext-
Appears in Collections:Master Degree / Yüksek Lisans Tezleri
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