Graph Convolutional Networks for context-aware recommender systems
Graph Convolutional Networks are powerful systems that allow representing complex structures such as user networks in recommendation scenarios. The goel of this master thesis is build a prototype and exploit its potential for its application to a recommender system.
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/327345 |
| Acceso en línea: | https://hdl.handle.net/2117/327345 |
| Access Level: | acceso abierto |
| Palabra clave: | recommender systems graph convolutional networks factorization machines context sistemas de recomendación contexto redes convolucionales de grafos |
| Sumario: | Graph Convolutional Networks are powerful systems that allow representing complex structures such as user networks in recommendation scenarios. The goel of this master thesis is build a prototype and exploit its potential for its application to a recommender system. |
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