Methods and metrics for cold-start recommendations
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Ontological user profiling in recommender systems
ACM Transactions on Information Systems (TOIS)
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
Web search personalization with ontological user profiles
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Tag-based user modeling for social multi-device adaptive guides
User Modeling and User-Adapted Interaction
A multilayer ontology-based hybrid recommendation model
AI Communications - Recommender Systems
Ontology-based news recommendation
Proceedings of the 2010 EDBT/ICDT Workshops
Ontology-based user modeling for knowledge management systems
UM'03 Proceedings of the 9th international conference on User modeling
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
The adaptive web
A feature and information theoretic framework for semantic similarity and relatedness
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
Analyzing cross-system user modeling on the social web
ICWE'11 Proceedings of the 11th international conference on Web engineering
Propagating user interests in ontology-based user model
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Gumo: the general user model ontology
UM'05 Proceedings of the 10th international conference on User Modeling
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We present an approach for propagation of user interests in ontology-based user models taking into account the properties declared for the concepts in the ontology. Starting from initial user feedback on an object, we calculate user interest in this particular object and its properties and further propagate user interest to other objects in the ontology, similar or related to the initial object. The similarity and relatedness of objects depends on the number of properties they have in common and their corresponding values. The approach we propose can support finer recommendation modalities, considering the user interest in the objects, as well as in singular properties of objects in the recommendation process. We tested our approach for interest propagation with a real adaptive application and obtained an improvement with respect to IS-A-propagation of interest values.