Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/4201
Title: An event-based Hidden Makrov Model approach to news classification and sequencing
Other Titles: Olay tabanlı Gizli Markov Modeli yaklaşımı ile haber sınıflandırması ve sıralaması
Authors: Tekir, Selma
Çavuş, Engin
Issue Date: 2014
Publisher: Izmir Institute of Technology
Abstract: Over 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.
Description: Thesis (Master)--Izmir Institute of Technology, Computer Engineering, Izmir, 2014
Includes bibliographical references (leaves: 28-29)
Text in English; Abstract: Turkish and English
vii, 32 leaves
URI: http://hdl.handle.net/11147/4201
Appears in Collections:Master Degree / Yüksek Lisans Tezleri

Files in This Item:
File Description SizeFormat 
10020653.pdfMasterThesis840.07 kBAdobe PDFThumbnail
View/Open
Show full item record

CORE Recommender

Page view(s)

32
checked on Jul 4, 2022

Download(s)

20
checked on Jul 4, 2022

Google ScholarTM

Check


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.