This diploma thesis is focused on content personalization and specifically on recommender systems. The aim of the thesis is to propose a methodology of recommender system implementation in e-commerce using the IT tool Soyka. Functions of personalization tools which directly support recommender systems are identified on the basis of a theoretical description of recommender systems and their technological approaches. Based on these identified functions the tool Soyka is classified. The main contribution of the thesis is the created and published methodology which is ready to be used on real implementation projects by anyone involved.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:358790 |
| Date | January 2017 |
| Creators | Müller, Petr |
| Contributors | Gála, Libor, Fanta, Michal |
| Publisher | Vysoká škola ekonomická v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0017 seconds