Workshop on Practical Use of Recommender Systems, Algorithms, and Technologies

This workshop contrived for a new uptake on past experiences and lessons learned from works on recommender systems. We proposed an analytic outlook on new research directions, or ones that still require substantial research, with a special focus on their practical adoption in working applications, and the barriers to be met in this path. The workshop explored gaps between academia and industry considering questions and topics such as the following: What are the main bottlenecks now? What is missing and what are the hot recommender system research topics for the next wave of computing? Is there already a killer application area, and if so, what are the technical and social (privacy, culture) issues we need to consider?

This workshop was an opportunity to bring together researchers and the industry to discuss, on one hand, the main lessons drawn from successes but also from failures of recommender systems, and on the other hand, identify and analyze the major research areas in recommendation and personalization technologies that should be addressed in the future for a practical, effective take-up of the needs of vendors, consumers, and technology providers.
One of the main goals of the workshop was to promote the discussion among the academic researchers and industry practitioners, so the format of the workshop favoured short papers.

  • Jérôme Picault, Bell Labs, Alcatel-Lucent
  • Dimitre Kostadinov, Bell Labs, Alcatel-Lucent
  • Pablo Castells, Universidad Autónoma de Madrid
  • Alejandro Jaimes, Yahoo! Research
Workshop Date

September 30, 2010

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