WPRS 2012 - 2012 International Workshop on Web Personalization and Recommender Systems (WPRS’12)

With the explosive growth of resources available through the Internet, information overload has become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Recommender and reputation systems represent tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years, driven by the demand for online personalization applications. Web-based recommender systems are the most notable application of web personalization. Combined with reputation systems, Web users can get recommendations with high reliability and quality. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from technology perspective and social perspective. Aim to promote high quality research in order to overcome these two challenges, this workshop will provide a forum for academic and industrial researchers to exchange understandings of past, present and future trends in Web personalization and recommendation making. The themes will be in algorithms, models, applications and interfaces.
Topics and areas include, but not limited to:
User behaviour modelling
Collaborative and content based filtering
Clustering in recommender systems
Hybrid recommender systems
Adaptive user interfaces and personalization techniques
Recommender systems in negotiation and auctions
Ontology learning and mining
Semantic Web Technologies
Measuring personalization effectiveness
Evaluation methods for recommender systems
Opinion mining for user behaviour models
Product modelling
Decision making in e-commerce systems
Data Warehousing in Business Intelligence
Web information gathering
Web mining
Explanation and justification in recommender systems
Distributed and peer?to?peer recommender systems
Reputation management in recommender systems
Security and trust in recommender systems
Recommender applications for social media sites
Social awareness and visualization