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Recommender systems challenge 2012

Published: 09 September 2012 Publication History

Abstract

The Recommender System Challenge 2012 invited participants to work on two tracks with real-world datasets and to submit their contributions that would be related to specific problem contexts. First of all, it asked participants to develop new algorithms and to compare them to other algorithms in given settings; in addition, it asked participants to explore with new recommendation methods, services, as well as added-value services related to recommendation.

References

[1]
Gediminas Adomavicius, Alexander Tuzhilin, Shlomo Berkovsky, Ernesto W. De Luca, and Alan Said, 'Context-awareness in recommender systems: research workshop and movie recommendation challenge', in Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, pp. 385--386, New York, NY, USA, (2010). ACM.
[2]
Kris Jack, James Hammerton, Dan Harvey, Jason J Hoyt, Jan Reichelt, and Victor Henning, 'Mendeley's reply to the datatel challenge', Procedia Computer Science, 1(2), 1--3, (2010).
[3]
Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, and Olga C. Santos, 'Recsystel preface 2010', Procedia Computer Science, 1(2), 2773 -- 2774, (2010). Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010).
[4]
Alan Said, Shlomo Berkovsky, and Ernesto W. De Luca, 'Putting things in context: Challenge on context-aware movie recommendation', in Proceedings of the Workshop on Context-Aware Movie Recommendation, CAMRa '10, pp. 2--6, New York, NY, USA, (2010). ACM.
[5]
Alan Said, Shlomo Berkovsky, and Ernesto W. De Luca, 'Group recommendation in context', in Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation, CAMRa '11, pp. 2--4, New York, NY, USA, (2011). ACM.
[6]
Alan Said, Shlomo Berkovsky, Ernesto William De Luca, and Jannis Hermanns, 'Challenge on context-aware movie recommendation: Camra2011', in Proceedings of the fifth ACM conference on Recommender systems, RecSys '11, pp. 385--386, New York, NY, USA, (2011). ACM.

Cited By

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  • (2021)Review text based rating prediction approaches: preference knowledge learning, representation and utilizationArtificial Intelligence Review10.1007/s10462-020-09873-y54:2(1171-1200)Online publication date: 1-Feb-2021
  • (2019)Explaining educational recommendations through a concept-level knowledge visualizationProceedings of the 24th International Conference on Intelligent User Interfaces: Companion10.1145/3308557.3308690(103-104)Online publication date: 16-Mar-2019
  • (2016)A Short History of the RecSys ChallengeAI Magazine10.1609/aimag.v37i4.269337:4(102-104)Online publication date: 1-Dec-2016
  • Show More Cited By

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Published In

cover image ACM Conferences
RecSys '12: Proceedings of the sixth ACM conference on Recommender systems
September 2012
376 pages
ISBN:9781450312707
DOI:10.1145/2365952
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: 09 September 2012

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Author Tags

  1. challenge
  2. competition
  3. context-aware
  4. dataset
  5. recommender systems
  6. scientific paper recommendation

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  • Technical-note

Conference

RecSys '12
Sponsor:
RecSys '12: Sixth ACM Conference on Recommender Systems
September 9 - 13, 2012
Dublin, Ireland

Acceptance Rates

RecSys '12 Paper Acceptance Rate 24 of 119 submissions, 20%;
Overall Acceptance Rate 85 of 414 submissions, 21%

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Cited By

View all
  • (2021)Review text based rating prediction approaches: preference knowledge learning, representation and utilizationArtificial Intelligence Review10.1007/s10462-020-09873-y54:2(1171-1200)Online publication date: 1-Feb-2021
  • (2019)Explaining educational recommendations through a concept-level knowledge visualizationProceedings of the 24th International Conference on Intelligent User Interfaces: Companion10.1145/3308557.3308690(103-104)Online publication date: 16-Mar-2019
  • (2016)A Short History of the RecSys ChallengeAI Magazine10.1609/aimag.v37i4.269337:4(102-104)Online publication date: 1-Dec-2016
  • (2016)Introduction to the Special Issue on Recommender System BenchmarkingACM Transactions on Intelligent Systems and Technology10.1145/28706277:3(1-4)Online publication date: 8-Mar-2016
  • (2016)Systematic approach for cold start issues in recommendations system2016 International Conference on Recent Trends in Information Technology (ICRTIT)10.1109/ICRTIT.2016.7569601(1-7)Online publication date: Apr-2016
  • (2016)Dealing with the new user cold-start problem in recommender systems: A comparative reviewInformation Systems10.1016/j.is.2014.10.00158(87-104)Online publication date: Jun-2016
  • (2016)Improving collaborative recommendations using vector quantization and clusteringSocial Network Analysis and Mining10.1007/s13278-016-0377-26:1Online publication date: 3-Sep-2016
  • (2015)HU-FCF++Engineering Applications of Artificial Intelligence10.1016/j.engappai.2015.02.00341:C(207-222)Online publication date: 1-May-2015
  • (2014)Recommender systems challenge 2014Proceedings of the 8th ACM Conference on Recommender systems10.1145/2645710.2645779(387-388)Online publication date: 6-Oct-2014
  • (2013)An application of fuzzy geographically clustering for solving the Cold-Start problem in recommender systems2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)10.1109/SOCPAR.2013.7054096(44-49)Online publication date: Dec-2013

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