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The Cross-Market Recommendation task of WSDM CUP 2022 is about findingsolutions to improve individual recommendation systems in resource-scarcetarget markets by leveraging data from similar high-resource source markets.Finally, our team OPDAI won the first place with NDCG@10 score of 0.6773 on theleaderboard. Our solution to this task will be detailed in this paper. Tobetter transform information from source markets to target markets, we adopttwo stages of ranking. In pre-ranking stage, we adopt diverse pre-rankingmethods or models to do feature generation. After elaborate feature analysisand feature selection, we train LightGBM with 10-fold bagging to do the finalranking.

An Effective Way for Cross-Market Recommendation with Hybrid Pre-Ranking and Ranking Models