Introduction to special section on CAMRa2010: Movie recommendation in context

Alan Said, Shlomo Berkovsky, Ernesto W. De Luca

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


The challenge and workshop on Context-Aware Movie Recommendation (CAMRa2010) were conducted jointly in 2010 with the Recommender Systems conference. The challenge focused on three context-aware recommendation scenarios: time-based, mood-based, and social recommendation. The participants were provided with anonymized datasets from two real-world online movie recommendation communities and competed against each other for obtaining the highest accuracy of recommendations. The datasets contained contextual features, such as tags, annotation, social relationsips, and comments, normally not available in public recommendation datasets. More than 40 teams from 21 countries participated in the challenge. Their participation was summarized by 10 papers published by the workshop, which have been extended and revised for this special section. In this preface we overview the challenge datasets, tasks, evaluation metrics, and the obtained outcomes.
Original languageEnglish
Article number13
Pages (from-to)1-9
Number of pages9
JournalACM Transactions on Intelligent Systems and Technology
Issue number1
Publication statusPublished - 2013
Externally publishedYes


  • Recommender systems
  • context-awareness
  • context-aware recommendations
  • social network analysis
  • user modeling
  • datasets


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