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Entity-Aware Collections Ranking: A Joint Scoring Approach

Published: 08 October 2024 Publication History

Abstract

Recommender systems in academia and industry typically predict Click-Through Rate (CTR) at the item or entity level. In practical scenarios, products can take on various forms and designs. We present a novel joint scoring framework that supports the listwise ranking of a collection composed of multiple entities. It learns the best combination of entities to be displayed to the user. We also introduce a novel dual attention mechanism that better captures the user’s interest in the collection. Our approach demonstrated superior performance through offline and online experiments and has been deployed to Shopee’s Shop Ads across all markets.

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cover image ACM Conferences
RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems
October 2024
1438 pages
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Published: 08 October 2024

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