Workshop on Large Scale Recommendation Systems

As we enter the era of Big Data, the modern Recommender System faces greatly increased data volume and complexities. Previous computational models and experience on small data may not hold today, thus, how to build an efficient and robust system has become an important issue for many practitioners. Meanwhile, there is an increasing gap between academia research of recommendation systems focusing on complex models, and industry practice focusing on solving problems at large scale using relatively simple techniques.

Chances favor connected minds. The motivation of this workshop is to bring together researchers and practitioners working on large-scale recommender system in order to: (1) share experience, techniques and methodologies used to develop effective large-scale recommender, from architecture, algorithm, programming model, to evaluation (2) identify key challenges and promising trends in the area, and (3) identify collaboration opportunities among participants.

  • Tao Ye (Pandora Internet Radio)
  • Quan Yuan (Taobao)
  • Danny Bickson (Carnegie Mellon University)
Workshop Date

Oct 13, 2013 (08:30 – 18:00)



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