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Paper Submission

Workshop Programme and Accepted Papers


The workshop proceedings is now available here.

The exponential growth of the social web poses challenges and new opportunities for recommender systems. The social web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their definition encourage interaction between users and both online content and other users, thus generating new sources of knowledge for recommender systems. Web 2.0 users explicitly provide personal information and implicitly express preferences through their interactions with others and the system (e.g. commenting, friending, rating, etc.). These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. The Social Web provides huge opportunities for recommender technology and in turn recommender technologies can play a part in fuelling the success of the Social Web phenomenon.

The goal of this workshop is to bring together researcher and practitioners to explore, discuss, and understand challenges and new opportunities for recommender systems and the Social Web. We solicit original contributions in the following areas:


  • Case studies and novel fielded social recommender applications
  • Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation.
  • Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.
  • Recommender systems mash-ups, Web 2.0 user interfaces, rich media recommender systems
  • Collaborative knowledge authoring, collective intelligence
  • Recommender applications involving users or groups directly in the recommendation process
  • Exploiting folksonomies, social network information, interaction, user context and communities or groups for recommendations
  • Trust and reputation aware social recommendations
  • Semantic Web recommender systems, use of ontologies or microformats
  • Empirical evaluation of social recommender techniques, success and failure  measures
  • Social recommender systems in the enterprise

Held in conjunction with ACM RecSys’11 on 23rd October in Chicago, IL, USA

3rd Workshop on Recommender Systems and the Social Web