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Master's Thesis
Author of thesis: Ing. Roman Kolář
Acad. year: 2007/2008
Supervisor: Ing. Vladimír Bartík, Ph.D.
Reviewer: doc. Ing. Radek Burget, Ph.D.
This paper presents problem of automatic webpages classification using association rules based classifier. Classification problem is presented, as a one of datamining technique, in context of mining knowledges from text data. There are many text document classification methods presented with highlighting benefits of classification methods using association rules.The main goal of work is adjusting selected classification method for relation data and design draft of webpages classifier, which classifies pages with the aid of visual properties - independent section layout on the web page, not (only) by textual data. There is also ARC-BC classification method presented as a selected method and as one of intriguing classificators, that derives accuracy and understandableness benefits of all other methods.
classification, classificator, Web, datamining, association rule, precission, data, discretization, category, structure, attribute, support, confidence, text, interval
Date of defence
17.06.2008
Result of the defence
Defended (thesis was successfully defended)
Grading
A
Language of thesis
Czech
Faculty
Fakulta informačních technologií
Department
Department of Information Systems
Study programme
Information Technology (IT-MSC-2)
Field of study
Information Systems (MIS)
Supervisor’s reportIng. Vladimír Bartík, Ph.D.
Grade proposed by supervisor: A
Reviewer’s reportdoc. Ing. Radek Burget, Ph.D.
Grade proposed by reviewer: A
Responsibility: Mgr. et Mgr. Hana Odstrčilová