ACM Conference on Recommender Systems 2015

Author: Benjamin Kille

In 2015, ACM RecSys took place from 16-20 September in Vienna, Austria. The conference featured two keynotes, five academic sessions, two industry sessions, four tutorials, and ten workshops. More than 450 attendees created a viable atmosphere actively exchanging ideas and engaging in discussions.

Frank Hopfgartner (University of Glasgow), Tobias Heintz (plista GmbH), Roberto Turrin (Contentwise), and I contributed a tutorial on stream-based recommender systems with real-time constraints. The tutorial highlighted requirements of industrial recommender systems in an attempt to bridge the gap between academic and industry perspectives on recommender systems.

Noteworthy Contributions

“It Takes Two to Tango: an Exploration of Domain Pairs for Cross-Domain Collaborative Filtering” by Shaghayegh Sahebi and Peter Brusilovsky. Link

Cross-Domain recommender systems use preferences spread across distinct item collections to enhance performance. The paper explores correlations among pairs of domains. The authors investigate how Canonical Correlation Analysis allows recommender systems to estimate how well cross-domain collaborative filtering will perform. Results obtained on data derived from Yelp indicate that injecting preferences from other domains improves rating prediction accuracy for most domain pairs.

“Predicting Online Performance of News Recommender Systems Through Richer Evaluation Metrics” by Andrii Maksai, Florent Garcin, and Boi Faltings. Link

Plenty of research on recommender systems measures performance in terms of rating prediction accuracy. This work introduces a multi-perspective view on news recommendations. The authors advocate considering various quality criteria simultaneously. Thereby, they predict how well a recommendation method will perform serving real users on a news portal. Their evaluation indicates that multiple criteria combined help predict online performances.

Industry Needs

RecSys featured two session of industry talks. Ten representatives of various companies described the problems they face on a daily basis. Uses cases included television, jobs, online contents/advertisements, vacation, and restaurants. The talks emphasized that operating recommender systems frequently face scenarios hardly reflected in academic research. Important aspects include scalability, response-time limitations, and lack of explicit preferences. Romain Lerallut and Diane Gasselin (Criteo) pointed out that their systems register 1 billion users and simultaneously have to keep 100ms response time limits. This setting renders highly sophisticated recommendation algorithms inapplicable.

Workshop Experience

RecSys hosted ten workshops. Workshops either highlighted a specific aspect or field of applications. Aspects included human factors (emotion, crowd sourcing, decision making, etc.), location-awareness, and scalability. Television, tourism, and news had a workshop each dedicated to their specificities.

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