Topics

The following are some of the issues and topics that will be addressed at the workshop.

• User Model representation: The use of domain knowledge and ontologies; user context definition and modeling; individual and group user models; cross-domain models; privacy; robust and trust-aware recommender systems; cognitive models for Web navigation and e-commerce interactions, psychological and sociological aspects of Recommender Systems; self-adaptation
• Preference Elicitation: knowledge acquisition methods, cognitive approaches, machine learning, data extraction methods, ontology integration, reconciliation of knowledge bases, knowledge elicitation.
• Architectures and Systems: personalized search; scalability of personalization and recommendation techniques; intelligent browsing and navigation; adaptive hypertext systems; architectures for personalized privacy; hybrid recommendation systems; conversational recommendation systems
• Enabling Technologies: Data/web mining for personalization; Link Analysis and Graph Mining; automated techniques for ontology generation, learning, and acquisition; machine leaning techniques for information extraction and integration; Web 2.0 and the Semantic Web; Evaluation methodologies, metrics, and case studies