Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Communications of the ACM
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
IEEE Transactions on Knowledge and Data Engineering
A multigranular linguistic content-based recommendation model: Research Articles
International Journal of Intelligent Systems
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
Information Sciences: an International Journal
The search for knowledge, contexts, and Case-Based Reasoning
Engineering Applications of Artificial Intelligence
Syskill & webert: Identifying interesting web sites
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Automatic properties adjusting method using user operations for local search smartphone applications
Proceedings of the International Working Conference on Advanced Visual Interfaces
A mobile 3D-GIS hybrid recommender system for tourism
Information Sciences: an International Journal
International Journal of Handheld Computing Research
Knowledge-Based Systems
Review: Mobile recommender systems in tourism
Journal of Network and Computer Applications
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Recommender systems have become a key tool in marketing processes in e-commerce, because they provide an added value to Web–based applications in order to keep customers. In the tourist sector, the use of tourist Web based sites has got a great success due to the fact that the easy integration of tourist business processes in Web based tools. In this contribution, we introduce a hybrid recommender system for restaurants, collaborative and knowledge-based, that is able to provide recommendations in any required situation by the users/customers; besides it provides information referred by Google Maps, regarding the recommendations. Such a system has been developed for our province, Jaén (Spain), but it can be easily extended for any other geographic area.