Recommender systems challenge 2014

Alan Said, Simon Dooms, Babak Loni, Domonkos Tikk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The 2014 ACM Recommender Systems Challenge invited re- searchers and practitioners to work towards a common goal, this goal being the prediction of users engagement in movie ratings expressed on Twitter. More than 200 participants sought to join the challenge and work on the new dataset released in its scope. The participants were asked to de- velop new algorithms to predict user engagement and evalu- ate them in a common setting, ensuring that the comparison was objective and unbiased, within the challenge.

Original languageEnglish
Title of host publicationRecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages387-388
Number of pages2
ISBN (Electronic)9781450326681
DOIs
Publication statusPublished - Oct 6 2014
Event8th ACM Conference on Recommender Systems, RecSys 2014 - Foster City, United States
Duration: Oct 6 2014Oct 10 2014

Publication series

NameRecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems

Other

Other8th ACM Conference on Recommender Systems, RecSys 2014
CountryUnited States
CityFoster City
Period10/6/1410/10/14

Keywords

  • Benchmarking
  • Challenge
  • Competition
  • Context-aware
  • Dataset
  • Recommender systems

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Said, A., Dooms, S., Loni, B., & Tikk, D. (2014). Recommender systems challenge 2014. In RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems (pp. 387-388). (RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/2645710.2645779