CARS ’11

3rd Workshop on Context-Aware Recommender Systems

This workshop has been built upon the success of the two previous editions held in conjunction with the 3rd and 4th ACM Conferences on Recommender Systems in 2009 and 2010.

The importance of contextual information has been recognized by researchers and practitioners in many disciplines, including e-commerce personalization, information retrieval, ubiquitous and mobile computing, data mining, marketing, and management. While a substantial amount of research has already been performed in the area of recommender systems, the vast majority of existing approaches focuses on recommending the most relevant items to users and does not take into account any additional contextual information, such as time, location, weather, or the company of other people.

In the last year a growing number of researchers have tried to address this limitation, but still the vast majority of the current solutions reduce the context model to a fixed set of contextual features that are used either to pre-filter the data used for building the prediction model or to post-filter the recommendations using the contextual conditions of the user. Therefore, this workshop aimed to bring together researchers with wide-ranging backgrounds to identify important research questions, to exchange ideas from different research disciplines, and, more generally, to facilitate discussion and innovation in the area of context-aware recommender systems (CARS).

  • Gediminas Adomavicius (University of Minnesota, USA)
  • Linas Baltrunas (Free University of Bozen-Bolzano, Italy)
  • Tim Hussein (University of Duisburg-Essen, Germany)
  • Francesco Ricci (Free University of Bozen-Bolzano, Italy)
  • Alexander Tuzhilin (New York University, USA)
Workshop Date

October 23, 2011

Web site