Putting Things in Context: Challenge on Context-Aware Movie Recommendation

被引:25
作者
Said, Alan [1 ]
Berkovsky, Shlomo [2 ]
De Luca, Ernesto W. [1 ]
机构
[1] Tech Univ Berlin, DAI Lab, Berlin, Germany
[2] CSIRO, Tasmanian ICT Ctr, Hobart, Tasmania, Australia
来源
PROCEEDINGS OF THE RECSYS'2010 ACM CHALLENGE ON CONTEXT-AWARE MOVIE RECOMMENDATION (CAMRA2010) | 2010年
关键词
Recommender systems; context-aware personalization; context modeling; social networks; datasets; social network analysis; user modeling; SYSTEMS;
D O I
10.1145/1869652.1869665
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Challenge on Context-Aware Movie Recommendation (CAMRa) was conducted as part of a join event on ContextAwareness in Recommender Systems at the 2010 ACM Recommender Systems conference. The challenge focused on three context-aware recommendation tasks: 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 recommendation accuracy for each task. The datasets contained contextual features, such as mood, plot annotation, social network, and comments, normally not available in movie recommendation datasets. Over 40 teams from 20 countries participated in the challenge. Their participation was summarized by 10 papers accepted to the CAMRa workshop.
引用
收藏
页码:2 / 6
页数:5
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