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RecSys '09: Proceedings of the third ACM conference on Recommender systems
ACM2009 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
RecSys '09: Third ACM Conference on Recommender Systems New York New York USA October 23 - 25, 2009
ISBN:
978-1-60558-435-5
Published:
23 October 2009
Sponsors:
In-Cooperation:

Reflects downloads up to 16 Oct 2024Bibliometrics
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Abstract

2009 is likely to become the "Year of the Netflix Challenge" in recommender systems. With a prize of one million dollars one of the highest in computer science, it raised a tremendous awareness for as well as a transformation to the field of recommender systems.

We are very happy to welcome you to the Third ACM Conference on Recommender Systems (ACM RecSys 2009) in New York. In the last few years, ACM RecSys has continuously grown and meanwhile certainly can be understood as the scientific core event in the area of recommender systems, bringing together persons from academic research, industry research as well as from applications. While recommender systems has close relations to many neighboring fields such as machine learning, information retrieval, databases, human computer interaction, e-commerce, semantic web and many others and many of the best conferences in these areas have their dedicated sessions on recommender systems, ACM RecSys is the conference where all of them finally meet.

With 187 submissions this year's ACM RecSys has continued to grow at a fast rate of over 50%. Authors from 35 different countries from all over the world submitted their papers. After the program committee consisting of 78 researchers finished a thorough scientific review process in two rounds writing almost 700 reviews, less than 19% of the long submissions have been accepted, the overall acceptance rate for long and short papers is less than 40%. Besides a deepened interest in algorithms for recommender systems, this year tags and social networks, privacy and security and trust attracted the most attention by authors.

Moreover, the program of ACM RecSys 2009 includes two keynotes, one from a more academic perspective and another one from a more industrial perspective, a panel session about the recently concluded Netflix challenge, three tutorials and three workshops as well as a doctoral symposium.

keynote
Recsys'09 industrial keynote: top 10 lessons learned developing deploying and operating real-world recommender systems

The number of online services providing users with real-time recommendations has increased exponentially over the last few years. Recommender Systems that were originally only accessible to a limited number of high-tech companies are now widely ...

keynote
Up close and personalized: a marketing view of recommendation systems

Developments in the marketing literature on recommendation systems are reviewed and an illustration of an Adaptive Personalization System is provided in the context of music. This illustration reveals that Adaptive Personalization Systems have the ...

research-article
Collaborative prediction and ranking with non-random missing data

A fundamental aspect of rating-based recommender systems is the observation process, the process by which users choose the items they rate. Nearly all research on collaborative filtering and recommender systems is founded on the assumption that missing ...

Contributors
  • IBM Thomas J. Watson Research Center
  • Leonard N. Stern School of Business
  • University of Colorado Boulder
  • Graz University of Technology
  • University of Hildesheim

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Acceptance Rates

Overall Acceptance Rate 254 of 1,295 submissions, 20%
YearSubmittedAcceptedRate
RecSys '191893619%
RecSys '181813218%
RecSys '171252621%
RecSys '161592918%
RecSys '151312821%
RecSys '15 Challenge211257%
RecSys '142343515%
RecSys '131363224%
RecSys '121192420%
Overall1,29525420%