@inproceedings{0b231c9e2a2f436d83622aae547701f1,
title = "Putting things in context: challenge on context-aware movie recommendation",
abstract = "The Challenge on Context-Aware Movie Recommendation (CAMRa) was conducted as part of a join event on Context-Awareness 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.",
keywords = "Recommender systems, context-aware personalization, context modeling, social networks, datasets, social network analysis, user modeling",
author = "Alan Said and Shlomo Berkovsky and {De Luca}, {Ernesto W.}",
year = "2010",
doi = "10.1145/1869652.1869665",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
pages = "2--6",
booktitle = "CAMRa '10 Proceedings of the Workshop on Context-Aware Movie Recommendation",
address = "United States",
note = "Workshop on Context-Aware Movie Recommendation, CAMRa '10 ; Conference date: 30-09-2010 Through 30-09-2010",
}