Sistema de recomendación de contenido de la plataforma On demand de Directv
Recommendation systems have been protagonists in modern content consumption systems and have become an important part of the industry, boosting sales volume based on personalized recommendations. The main priority of these systems is to facilitate decision-making by users. When there are many option...
| Autores: | , |
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | Colombia |
| Institución: | Universidad de los Andes |
| Repositorio: | Séneca: repositorio Uniandes |
| Idioma: | español |
| OAI Identifier: | oai:repositorio.uniandes.edu.co:1992/51031 |
| Acceso en línea: | http://hdl.handle.net/1992/51031 |
| Access Level: | acceso abierto |
| Palabra clave: | Sistemas de recomendación Vídeo bajo demanda Redes neurales (Computadores) DirecTV (Organización) Ingeniería |
| Sumario: | Recommendation systems have been protagonists in modern content consumption systems and have become an important part of the industry, boosting sales volume based on personalized recommendations. The main priority of these systems is to facilitate decision-making by users. When there are many options to choose from, choosing a content or product is more complex compared to having few options. It is key to reduce the amount of products that customers are exposed to, and it is even more important to know how to present the right products, since it is very likely that sales will increase. In this document, a recommendation system for Directv's on demand platform will be presented. Throughout the document, the diferent stages of the system's development will be presented, including the data ingestion phase, extraction of auxiliary data, analysis and interpretation of the results. |
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