CFP: RecSys 2011 Challenge on Context-aware Movie Recommendation - CAMRa2011

[Alan Said]

CALL FOR PAPERS AND PARTICIPATION

CAMRa2011 :: Challenge on Context-aware Movie Recommendation in conjunction with the 2011 ACM Recommender Systems Conference, Chicago, IL, USA, October 23-27, 2011

URL: http://www.camrachallenge.com

General Information:

Following the success of CAMRa2010, we are pleased to announce this year's Challenge on Context-Aware Movie Recommendation.The majority of existing recommendation approaches does not take into account contextual information, such as time, location, or weather. This challenge aims to tackle the practical issue of context-aware movie recommendation. A new movie rating datasete from Moviepilot will be released for the challenge. The dataset contains a number of contextual features, typically not found in standard collaborative filtering datasets. The participating teams are requested to use the additional contextual features to generate context-aware recommendations.

The challenge focuses on classification accuracy metrics. The participants are invited to submit papers focusing on the challenge to the workshop, which will be conducted in conjunction with RecSys2011.

Challenge:

The challenge consists of two tracks: in the first track, the participants are requested to generate recommendations for households, in the second the focus lies on identifying which member of a household performed a specific rating. The dataset is anonymized to protect the users of each service. Participants are expected to use the provided dataset; the use of external information sources, like IMDB, Wikipedia, or NetFlix, is not allowed.

The evaluations should address the following metrics: MAP, P@5, P@10, and AUC. The performance of the teams will be published on an online leaderboard. Additional datasets will be released for the final evaluation to identify the winners of each track. An online evaluation with real users will be conducted during the final week of the challenge.

Dataset (available end of May):

To access the datasets, please send an inquiry stating which dataset(s) you request, your affiliation, and which track(s) you intend to participate in to camr...@camrachallenge.com. The request will help the organizers to estimate the number of participants.

Call for Papers:

The participants are invited to submit papers focusing on the challenge and algorithms evaluated using the released datasets. The submissions are limited to 8 pages in the ACM SIG proceedings format. The papers will be reviewed by the Program Committee based on significance, technical soundness, and presentation clarity. Additionally, the creativity, originality, and scalability will be given special significance during the review process.

Paper submissions and reviews will be handled electronically through the CAMRa page in EasyChair which will be made available in due time for the deadlines.

Important dates:

Dataset Released: May, 2011

Paper Submission: July 25th, 2011

Notification: August 19th, 2011

Camera-ready submission: September 15th, 2011 Winners announces: RecSys Banquet 

Organizers and Committees:

General Chairs (camr...@camrachallenge.com):

Alan Said, DAI Lab/Technische Universität Berlin 

Shlomo Berkovsky, CSIRO 

Ernesto William De Luca, DAI Lab/Technische Universität Berlin 

Jannis Hermanns, Moviepilot

Program Committee (preliminary)

Sarab Anand, University of Warwick, England 

Linas Baltrunas, Free University of Bozen Bolzano, Italy 

Toine Bogers, Royal School of Library and Information Science, Denmark 

Ido Guy, IBM, Israel 

Tom Heath, Talis, England

Tim Hussein, University of Duisburg-Essen, Germany 

Dietmar Jannach, Technische Universität Dortmund, Germany 

Robert Jäschke, University of Kassel, Germany 

Alexandros Karatzoglou, Telefonica Research, Spain 

Neal Lathia, University College London, England 

Kevin McCarthy, University College Dublin, Ireland

Bamshad Mobasher, DePaul University, USA

Till Plumbaum, TU-Berlin, Germany 

Bracha Shapira, Ben-Gurion University of the Negev, Israel 

Markus Schedl, Johannes Kepler University Linz, Austria 

Qiang Yang, Hong Kong University of Science and Technology, Hong Kong

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M.Sc.(Eng.) Alan Said

Competence Center Information Retrieval & Machine Learning Technische Universität Berlin DAI-Labor Sekr. TEL 14 Ernst-Reuter-Platz 7

10587 Berlin / Germany

Phone:  0049 - 30 - 314 74072

Fax:    0049 - 30 - 314 74003

E-mail: alan...@dai-labor.de

http://www.dai-labor.de

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