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Attention Weighted Mixture of Experts with Contrastive Learning for Personalized Ranking in E-commerce
An effective ranking model should give a personalized ranking list for each user according to the user preference.
A unified Neural Network Approach to E-CommerceRelevance Learning
We describe a highly-scalable feed-forward neural model to provide relevance score for (query, item) pairs, using only user query and item title as features, and both user click feedback as well as limited human ratings as labels.
From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
We introduce deep learning models to the two most important stages in product search at JD. com, one of the largest e-commerce platforms in the world.
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