Keping Yang
3 papers in the PaperMetrix corpus
Papers by this author
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SDM
2019
Capturing users' precise preferences is a fundamental problem in large-scale recommender system. Currently, item-based Collaborative Filtering (CF) methods are common matching approaches in industry. However, they are not effective to model dynamic and evolving preferences …
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Deep Session Interest Network for Click-Through Rate Prediction
2019
Click-Through Rate (CTR) prediction plays an important role in many industrial applications, such as online advertising and recommender systems. How to capture users' dynamic and evolving interests from their behavior sequences remains a continuous research …
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AutoDebias: Learning to Debias for Recommendation
2021
Recommender systems rely on user behavior data like ratings and clicks to build personalization model. However, the collected data is observational rather than experimental, causing various biases in the data which significantly affect the learned …