Property-based collaborative filtering for health-aware recommender systems
Abstract:
Recommender systems aim at solving the problem of information overload by selecting items (commercial products, educational assets, TV programs, etc.) that match the consumers' interests and preferences. Recently, there have been approaches to drive the recommendations by the information stored in electronic health records, for which the traditional strategies applied in online shopping, e-learning, entertainment and other areas have several pitfalls. This paper addresses those problems by introducing a new filtering strategy, centered on the properties that characterize the items and the users. Preliminary experiments with real users have proved that this approach outperforms previous ones in terms of consumers' satisfaction with the recommended items. The benefits are especially apparent among people with specific health concerns. © 2011 Elsevier Ltd. All rights reserved.
Año de publicación:
2012
Keywords:
- COLLABORATIVE FILTERING
- semantics
- recommender systems
- Electronic health records
Fuente:
Tipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
- Aprendizaje automático
- Ciencias de la computación
Áreas temáticas:
- Funcionamiento de bibliotecas y archivos