The main goal of the thesis is to explore basic methods which can be used to find semantically related scientific articles. All the methods are explained in detail, compared and in the end evaluated by the standard metrics. Based on the evaluation, a new method for computing semantic similarity of scientific articles is proposed. The proposed method is based on the current state-of-the-art methods and adds the another important factor for computing similarity - citations. Using citations is important, since they represent a static bond between the articles. Finally, the proposed method is evaluated on the real data and compared with other described methods.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:236920 |
| Date | January 2011 |
| Creators | Dresto, Erik |
| Contributors | Schmidt, Marek, Otrusina, Lubomír |
| Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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