Thesis Details
Klasifikace webových stránek
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
Burget Radek, doc. Ing., Ph.D. (DIFS FIT BUT), člen
Matoušek Petr, doc. Ing., Ph.D., M.A. (DIFS FIT BUT), člen
Motyčka Arnošt, doc. Ing., CSc. (Mendelu), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
Vojnar Tomáš, prof. Ing., Ph.D. (DITS FIT BUT), člen
@mastersthesis{FITMT6625,
author = "Roman Kol\'{a}\v{r}",
type = "Master's thesis",
title = "Klasifikace webov\'{y}ch str\'{a}nek",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2008,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/6625/"
}