Thesis title: |
Ontology Learning and Information Extraction for the Semantic Web |
Author: |
Kavalec, Martin |
Thesis type: |
Dissertation thesis |
Supervisor: |
Berka, Petr |
Opponents: |
Burešová, Olga |
Thesis language: |
English |
Abstract: |
The work gives overview of its three main topics: semantic web,
information extraction and ontology learning. A method for
identification relevant information on web pages is described and
experimentally tested on pages of companies offering products and
services. The method is based on analysis of a sample web pages and
their position in the Open Directory catalogue.
Furthermore, a modfication of association rules mining algorithm is
proposed and experimentally tested. In addition to an identification
of a relation between ontology concepts, it suggest possible naming of
the relation. |
Keywords: |
ontology learning; information extraction; association rules; natural language processing; semantic web |
Information about study
Study programme: |
Aplikovaná informatika/Informatika |
Type of study programme: |
Doktorský studijní program |
Assigned degree: |
Ph.D. |
Institutions assigning academic degree: |
Vysoká škola ekonomická v Praze |
Faculty: |
Faculty of Informatics and Statistics |
Department: |
Department of Information and Knowledge Engineering |
Information on submission and defense
Date of assignment: |
4. 9. 2006 |
Date of submission: |
4. 9. 2006 |
Date of defense: |
2016 |
Files for download
The files will be available after the defense of the thesis.