XMRec: Workshop on Cross-Market Recommendation

Open Access
Authors
  • J. Allan
  • V. Murdock
Publication date 2021
Book title RECSYS 2021
Book subtitle 15th ACM Conference on Recommender Systems : 27th September-1st October 2021, Amsterdam, Netherlands
ISBN (electronic)
  • 9781450384582
Event 15th ACM Conference on Recommender Systems (RECSYS)
Pages (from-to) 817-818
Publisher New York, New York: The Association for Computing Machinery
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
Online markets are spreading quickly across the globe, supporting a huge network of product sales to billions of customers with various cultures, lifestyles, economic interests, and languages. These global markets introduce many novel opportunities—as well as challenges. Our workshop, called XMRec, concerns the problem of recommending relevant products to users in a target market (e.g., a resource-scarce market) by leveraging data from similar high-resource markets, e.g. using data from the U.S. market to improve recommendations in a target market. We hypothesize that data from one market can be used to improve recommendation in another. We aim to create a dynamic and interactive atmosphere where researchers of diverse backgrounds and interests can discuss their ideas on cross-market recommendation and how it can be further pursued in the community. To this end, XMRec features a series of seed talks both from industry and academia, discussing the future of cross-market recommendation and its potentials as a new line of research. The seed talks will be followed by a panel discussion where a diverse set of researchers discuss their ideas and opinion about the topic. Finally, we will invite the participants and the panelists to take part in interactive brainstorming breakout sessions to further discuss their ideas. We aim to motivate a range of studies (like analyzing market-specific biases, conversational recommendation, and predicting early adopters) beyond the cross-domain recommendation by extending markets and content languages.
Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3460231.3470934
Downloads
3460231.3470934 (Final published version)
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