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Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks.

, , , , , , and . KDD, page 596-605. ACM, (2018)

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Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks., , , , , , and . KDD, page 596-605. ACM, (2018)Text Matching Indexers in Taobao Search., , , , , and . KDD, page 5339-5350. ACM, (2024)Nonlinear Compressed Sensing-Based LDA Topic Model for Polarimetric SAR Image Classification., , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 7 (3): 972-982 (2014)Adversarial Multimodal Representation Learning for Click-Through Rate Prediction., , , , , and . WWW, page 827-836. ACM / IW3C2, (2020)Large Language Model based Long-tail Query Rewriting in Taobao Search., , , , , , , , and . WWW (Companion Volume), page 20-28. ACM, (2024)Self-Supervised Learning on Users' Spontaneous Behaviors for Multi-Scenario Ranking in E-commerce., , , , , , , , and . CIKM, page 3828-3837. ACM, (2021)Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search., , , , , , , , , and . WSDM, page 262-270. ACM, (2022)Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce., , , , , and . KDD, page 5398-5408. ACM, (2024)