Ontology Learning and Information Extraction for the Semantic Web
| Thesis title: | Ontology Learning and Information Extraction for the Semantic Web |
|---|---|
| Author: | Kavalec, Martin |
| Thesis type: | Dissertation thesis |
| Supervisor: | Berka, Petr |
| Opponents: | Štěpánková, Olga; Snášel, Václav |
| 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; semantic web; natural language processing; association rules |
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: | - |
|---|---|
| Date of submission: | - |
| Date of defense: | 18. 9. 2006 |
| Identifier in the InSIS system: |