Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
User Modeling for Adaptive News Access
User Modeling and User-Adapted Interaction
Centroid-Based Document Classification: Analysis and Experimental Results
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Evaluating adaptive user profiles for news classification
Proceedings of the 9th international conference on Intelligent user interfaces
Google news personalization: scalable online collaborative filtering
Proceedings of the 16th international conference on World Wide Web
Comparing and evaluating information retrieval algorithms for news recommendation
Proceedings of the 2007 ACM conference on Recommender systems
Media Meets Semantic Web --- How the BBC Uses DBpedia and Linked Data to Make Connections
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Personalized news recommendation based on click behavior
Proceedings of the 15th international conference on Intelligent user interfaces
Content-based recommendation systems
The adaptive web
Learning to model relatedness for news recommendation
Proceedings of the 20th international conference on World wide web
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In this paper we introduce the project of our PhD thesis. The subject is a model for news articles filtering. We propose a framework combining information about named entities extracted from news articles with article texts. Named entities are enriched with additional attributes crawled from semantic web resources. These properties are then used to enhance the filtering results. We described various ways of a user profile creation, using our model. This should enable news filtering covering any specific user needs. We report on some preliminary experiments and propose a complex experimental environment and different measures.