User models: theory, method, and practice
International Journal of Man-Machine Studies
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Computer Supported Social Networking For Augmenting Cooperation
Computer Supported Cooperative Work
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
Recommending collaboration with social networks: a comparative evaluation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
Document recommendation for knowledge sharing in personal folder environments
Journal of Systems and Software
Improving Text Classification by Using Encyclopedia Knowledge
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
SoRec: social recommendation using probabilistic matrix factorization
Proceedings of the 17th ACM conference on Information and knowledge management
Editorial: Hybrid learning machines
Neurocomputing
On social networks and collaborative recommendation
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Learning to recommend with social trust ensemble
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Logic-oriented neural networks for fuzzy neurocomputing
Neurocomputing
Editorial: Hybrid intelligent algorithms and applications
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Extended latent class models for collaborative recommendation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A semantic-based social network of academic researchers
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
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We present a hybrid method for an expert recommendation system that integrates the characteristics of content-based recommendation algorithms into a social network-based collaborative filtering system. Our method aims at improving the accuracy of the recommendation prediction by considering the social aspect of experts' behaviors. For this purpose, social communities of experts are first detected by applying social network analysis and using factors such as experience, background, knowledge level, and personal preferences of experts. Representative members of communities are then identified using a network centrality measure. Finally, a recommendation is made to relate an information item, for which a user is seeking for an expert, to the representatives of the most relevant community. Further from an expert's perspective, she/he has been suggested to work on relevant information items that fall under her/his expertise and interests.