Topics

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

• Systems and Algorithms Recommender systems for and personalization of the social Web including Folksonomies and social networks; personalized search and resource discovery; intelligent agents for browsing and navigation; recommender system mashups; privacy-preserving personalization methods; robust and trust-aware recommender systems; hybrid recommender system; ensemble methods for collaborative recommendations; conversational recommendation systems; dynamics of recommendation; user studies and empirical evaluation of systems; practical applications and case studies of deployed recommender and personalization systems.
• User Modeling and Preference Elicitation The use of domain knowledge and ontologies in user modeling; contextual and task-oriented recommender interfaces and algorithms; individual and group user models / group recommendation; cross-domain models; automated techniques for user profile generation and updating; trust and reputation in user modeling and recommendation; cognitive models for Web navigation and e-commerce interactions, psychological and sociological aspects of recommender systems; self-adaptation; utility function elicitation from implicit and explicit user interaction; data models for Web usage, content, and structure; latent factor models for user profiling; natural language models.
• 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 filtering, extraction and integration; learning metadata and harvesting; Web 2.0 and Semantic Web technologies; ubiquitous environments; collaborative knowledge authoring and collective intelligence; mining recommendation knowledge from the Social Web.