Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
Digital Identity
An LDAP-based User Modeling Server and its Evaluation
User Modeling and User-Adapted Interaction
Harvesting with SONAR: the value of aggregating social network information
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mediation of user models for enhanced personalization in recommender systems
User Modeling and User-Adapted Interaction
RSS-Based Interoperability for User Adaptive Systems
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
User identification for cross-system personalisation
Information Sciences: an International Journal
Semantic Modelling of User Interests Based on Cross-Folksonomy Analysis
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Ontologically-Enriched unified user modeling for cross-system personalization
UM'05 Proceedings of the 10th international conference on User Modeling
A framework for browsing, manipulating and maintaining interoperable learner profiles
UM'05 Proceedings of the 10th international conference on User Modeling
Journal of Information Science
Personal learning environments on the Social Semantic Web
Semantic Web - Linked Data for science and education
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This paper presents an approach to uniquely identify users and to retrieve their data distributed in profiles stored in different systems. The objective is exploiting the public user data available in the Web and especially in social networks. The approach does not require the implementation of specific protocols and the provision of authentication data. The evaluation provides good results that encourage us in carrying on the extension of the project. The extension we are working on is aimed at aggregating, using heuristic techniques, the data stored in the retrieved profiles and at inferring new data about the user.