Dynamic adaptation of hypertext structure
HYPERTEXT '91 Proceedings of the third annual ACM conference on Hypertext
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
User-Driven Ontology Evolution Management
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Usage-Oriented Evolution of Ontology-Based Knowledge Management Systems
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Ontological user profiling in recommender systems
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Ontology mapping: the state of the art
The Knowledge Engineering Review
Reducing OWL entailment to description logic satisfiability
Web Semantics: Science, Services and Agents on the World Wide Web
Towards open decision support systems based on semantic focused crawling
Expert Systems with Applications: An International Journal
Alignment-Based Preprocessing of Personal Ontologies on Semantic Social Network
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
A survey of Web clustering engines
ACM Computing Surveys (CSUR)
Requirements-oriented methodology for evaluating ontologies
Information Systems
Requirements-oriented methodology for evaluating ontologies
Information Systems
Adaptive systems in the era of the semantic and social web, a survey
User Modeling and User-Adapted Interaction
User profiles for personalized information access
The adaptive web
A semantic query approach to personalized e-catalogs service system
Journal of Theoretical and Applied Electronic Commerce Research
Concept drift and how to identify it
Web Semantics: Science, Services and Agents on the World Wide Web
Winnowing ontologies based on application use
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Evaluation of ontology enhancement tools
EWMF'05/KDO'05 Proceedings of the 2005 joint international conference on Semantics, Web and Mining
Sense induction in folksonomies: a review
Artificial Intelligence Review
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Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogenous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. Of particular interest for supporting users during the personalization are collaborative filtering systems which can produce personal recommendations by computing the similarity between own preferences and the one of other people. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.