Intelligent Systems for Tourism
IEEE Intelligent Systems
Jess in Action: Java Rule-Based Systems
Jess in Action: Java Rule-Based Systems
The Long Tail: Why the Future of Business Is Selling Less of More
The Long Tail: Why the Future of Business Is Selling Less of More
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Learning preferences of new users in recommender systems: an information theoretic approach
ACM SIGKDD Explorations Newsletter
Photo-based user profiling for tourism recommender systems
EC-Web'07 Proceedings of the 8th international conference on E-commerce and web technologies
Case-based recommender systems: a unifying view
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
How random walks can help tourism
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
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Obtaining information which is both trustworthy and relevant to the user is crucial for the success of the Travel Recommender Systems. Such a system should automatically obtain high quality facts and knowledge about the touristic attractions, filter them and present the user only those pieces which are of interest for him. To this end, a challenging issue is to select among the existing technologies those able to be articulated into a system which could fulfill the mentioned task. The system we propose has a pragmatic approach of the problem, aiming to identify the instruments to be used in touristic information gathering, if integrated in such a system. The system is built around a map system and a general purpose ontology and makes use of parsing techniques in order to retrieve additional information from web sources via a search engine. The proposed architecture is also expandable and other technologies can be linked to improve the variety of results.