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abstract

Second Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2015)

Published: 16 September 2015 Publication History

Abstract

While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2015 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.

References

[1]
T. Bogers, M. Koolen, and I. Cantador, editors. Proceedings of the 1st Workshop on New Trends in Content-based Recommender Systems, co-located with the 8th ACM Conference on Recommender Systems, CBRecSys@RecSys 2014, Foster City, Silicon Valley, California, USA, October 6, 2014, volume 1245 of CEUR Workshop Proceedings. CEUR-WS.org, 2014.
[2]
T. Bogers, M. Koolen, and I. Cantador. Workshop on New Trends in Content-based Recommender Systems: (CBRecSys 2014). In Eighth ACM Conference on Recommender Systems, RecSys '14, Foster City, Silicon Valley, CA, USA - October 06 - 10, 2014, pages 379--380, 2014.
[3]
T. Bogers, M. Koolen, and I. Cantador. Report on RecSys 2014 Workshop on New Trends in Content-Based Recommender Systems. ACM SIGIR Forum, 2015.
[4]
G. Dror, N. Koenigstein, Y. Koren, and M. Weimer. The Yahoo! Music Dataset and KDD-Cup '11. In JMLR Workshop and Conference Proceedings, volume 18 of Proceedings of KDD Cup 2011, pages 3--18. Springer, 2012.
[5]
P. Lops, M. de Gemmis, and G. Semeraro. Content-based Recommender Systems: State of the Art and Trends. In Recommender Systems Handbook, pages 73--105. Springer, 2011.
[6]
I. Pilászy and D. Tikk. Recommending New Movies: Even a Few Ratings Are More Valuable Than Metadata. In RecSys '09: Proceedings of the Third ACM Conference on Recommender Systems, pages 93--100. ACM, 2009.

Cited By

View all
  • (2020)Surprise: A Python library for recommender systemsJournal of Open Source Software10.21105/joss.021745:52(2174)Online publication date: Aug-2020
  • (2016)Third Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2016)Proceedings of the 10th ACM Conference on Recommender Systems10.1145/2959100.2959200(419-420)Online publication date: 7-Sep-2016

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  1. Second Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2015)

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      cover image ACM Conferences
      RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems
      September 2015
      414 pages
      ISBN:9781450336925
      DOI:10.1145/2792838
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 16 September 2015

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      Author Tags

      1. content-based recommendation
      2. context
      3. implicit feedback
      4. recommender systems
      5. semantics
      6. text reviews
      7. user-generated contents

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      RecSys '15
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      RecSys '15: Ninth ACM Conference on Recommender Systems
      September 16 - 20, 2015
      Vienna, Austria

      Acceptance Rates

      RecSys '15 Paper Acceptance Rate 28 of 131 submissions, 21%;
      Overall Acceptance Rate 254 of 1,295 submissions, 20%

      Upcoming Conference

      RecSys '24
      18th ACM Conference on Recommender Systems
      October 14 - 18, 2024
      Bari , Italy

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      Cited By

      View all
      • (2020)Surprise: A Python library for recommender systemsJournal of Open Source Software10.21105/joss.021745:52(2174)Online publication date: Aug-2020
      • (2016)Third Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2016)Proceedings of the 10th ACM Conference on Recommender Systems10.1145/2959100.2959200(419-420)Online publication date: 7-Sep-2016

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