GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Application of Spreading Activation Techniques in InformationRetrieval
Artificial Intelligence Review
A personal news agent that talks, learns and explains
Proceedings of the third annual conference on Autonomous Agents
Modern Information Retrieval
Understanding and Using Context
Personal and Ubiquitous Computing
User Modeling for Adaptive News Access
User Modeling and User-Adapted Interaction
Personalised Delivery of News Articles from Multiple Sources
ECDL '00 Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
PENS: A Personalized Electronic News System
CNSR '05 Proceedings of the 3rd Annual Communication Networks and Services Research Conference
IEEE Transactions on Knowledge and Data Engineering
Context-aware, Ontology-based Recommendations
SAINT-W '06 Proceedings of the International Symposium on Applications on Internet Workshops
Open user profiles for adaptive news systems: help or harm?
Proceedings of the 16th international conference on World Wide Web
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
From Web to Social Web: Discovering and Deploying User and Content Profiles
Context-aware recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
A multilayer ontology-based hybrid recommendation model
AI Communications - Recommender Systems
Semantic Modelling of User Interests Based on Cross-Folksonomy Analysis
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Ontology-Based Personalised and Context-Aware Recommendations of News Items
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Personalized recommendation on dynamic content using predictive bilinear models
Proceedings of the 18th international conference on World wide web
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
Personalized Content Retrieval in Context Using Ontological Knowledge
IEEE Transactions on Circuits and Systems for Video Technology
Collaborative filtering by analyzing dynamic user interests modeled by taxonomy
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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Recommender systems have achieved success in a variety of domains, as a means to help users in information overload scenarios by proactively finding items or services on their behalf, taking into account or predicting their tastes, priorities, or goals. Challenging issues in their research agenda include the sparsity of user preference data and the lack of flexibility to incorporate contextual factors in the recommendation methods. To a significant extent, these issues can be related to a limited description and exploitation of the semantics underlying both user and item representations. The authors propose a three-fold knowledge representation, in which an explicit, semantic-rich domain knowledge space is incorporated between user and item spaces. The enhanced semantics support the development of contextualisation capabilities and enable performance improvements in recommendation methods. As a proof of concept and evaluation testbed, the approach is evaluated through its implementation in a news recommender system, in which it is tested with real users. In such scenario, semantic knowledge bases and item annotations are automatically produced from public sources.