Thesis Details
Strojové učení v přirozeném jazyce
This beachelor's thesis deals with word sense disambiguation problem using the machine learning techniques. There are shortly presented problems of word sense disambiguation and its timeline. There are described methods and approaches, especially the naive Bayes classifier that is implemented in the system. There's illustrated a simple example of using this classifier. In a practical section is described project of system based on naive Bayes classifier including description of various algorithms used in the system. Finally there are described evaluation and analysis of the system. This created system took part in an international competition on semantic evaluation workshop SemEval-2007.
machine learning, supervised learning, natural language processing, word sense disambiguation, naive Bayes classifier, Senseval, Semeval
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Kreslíková Jitka, doc. RNDr., CSc. (DIFS FIT BUT), člen
Pelikán Jaroslav, RNDr., Ph.D. (FI MUNI), člen
Zbořil František, doc. Ing., Ph.D. (DITS FIT BUT), člen
Zemčík Pavel, prof. Dr. Ing. (DCGM FIT BUT), člen
@bachelorsthesis{FITBT5801,
author = "Lubom\'{i}r Otrusina",
type = "Bachelor's thesis",
title = "Strojov\'{e} u\v{c}en\'{i} v p\v{r}irozen\'{e}m jazyce",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2007,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/5801/"
}