This work deals with creating a hybrid system based on the aggregation of artificial immune system with appropriate heuristics to make the most effective spam detection. This work describes the main principles of biological and artificial immune system and conventional techniques to detect spam including several classifiers. The developed system is tested using well known database corpuses and a comparison of the final experiments is made.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:237087 |
| Date | January 2011 |
| Creators | Hohn, Michal |
| Contributors | Sekanina, Lukáš, Schwarz, Josef |
| 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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