IRLabers Mohammad Aliannejadi, Ali Vardasbi, and Evangelos Kanoulas together with Hamed Bonab and James Allan from University of Massachusetts Amherst are organising a WSDM 2022 Cup, titled “Cross-Market Item Recommendation”.
E-commerce companies often operate across markets; for instance Amazon has expanded their operations and sales to 18 markets (i.e. countries) around the globe. The cross-market recommendation 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. The key challenge, however, is that data, such as user interaction data with products (clicks, purchases, reviews), convey certain biases of the individual markets. Therefore, the algorithms trained on a source market are not necessarily effective in a different target market. Despite its significance, small progress has been made in cross-market recommendation, mainly due to a lack of experimental data for the researchers. In this WSDM Cup challenge, user purchase and rating data are provided on various markets with a considerable number of shared item subsets. The goal is to improve individual recommendation systems in these target markets by leveraging data from similar auxiliary markets.
Check out the website for more details: https://xmrec.github.io/wsdmcup/.
To participate, register on Codalab: https://competitions.codalab.org/competitions/360506:54.
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