Exploiting digital TV users' preferences in a tourism recommender system based on semantic reasoning
Abstract:
Tourism recommender systems match the user preferences against the huge diversity of tourist resources, helping to decide where to go and what to do. Current approaches require the users to initialize manually their profiles by expressing their interests accurately, which is a very tedious process. We propose a system that automatically infers the users' preferences from their TV viewing histories, i.e., the tourism resources the users might appreciate are selected by considering the TV contents they enjoyed in the past. To this aim, we have developed a context-aware semantics-based recommendation strategy that considers both the users' preferences and the interests of like-minded individuals. The resulting recommendations shape a tailormade on-move travel plan the users can access via (domestic and) handheld consumer devices. © 2006 IEEE.
Año de publicación:
2010
Keywords:
- digital TV
- semantic web
- Context-aware recommender systems
- WEB SERVICES
- personalized tourism
Fuente:
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Tipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
- Inteligencia artificial
- Ciencias de la computación
Áreas temáticas:
- Métodos informáticos especiales
- Procesos sociales
- Producción