User models: theory, method, and practice
International Journal of Man-Machine Studies
Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Building efficient and effective metasearch engines
ACM Computing Surveys (CSUR)
The State of the Art in Text Filtering
User Modeling and User-Adapted Interaction
Machine Learning for User Modeling
User Modeling and User-Adapted Interaction
Collaborative filtering via gaussian probabilistic latent semantic analysis
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
An intelligent search agent system for semantic information retrieval on the internet
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
Personalized social & real-time collaborative search
Proceedings of the 16th international conference on World Wide Web
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
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In this paper, we propose an XML-based recommender system, called SPGProfile. It is a type of collaborative information filtering system. SPGProfile uses ontology-driven social networks, where nodes represent social groups. A social group is an entity that defines a group based on demographic, ethnic, cultural, religious, age, or other characteristics. In the SPGProfile framework, query results are filtered and ranked based on the preferences of the social groups to which the user belongs. If the user belongs to social group G"x, results will be filtered based on the preferences of G"x and the preferences of each ancestor social group of G"x in the social network. SPGProfile can be used for various practical applications, such as Internet or other businesses that market preference-driven products. In the ontology, the preferences of a social group are identified from either: (1) the preferences of its member users or (2) from published studies about the social group. We describe and experimentally compare these two approaches. We also experimentally evaluate the search effectiveness and efficiency of SPGProfile and compare it to two existing search engines.