Jiarui Qin
6 papers in the PaperMetrix corpus
Papers by this author
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Retrieval & Interaction Machine for Tabular Data Prediction
2021 · arXiv (Cornell University)
Prediction over tabular data is an essential task in many data science applications such as recommender systems, online advertising, medical treatment, etc. Tabular data is structured into rows and columns, with each row as a …
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GraphHINGE: Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network
2020 · arXiv (Cornell University)
Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations. Recent attempts either rely on explicit path reachability to leverage path-based semantic relatedness or graph neighborhood to …
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Unleashing the Potential of Multi-Channel Fusion in Retrieval for Personalized Recommendations
2024 · arXiv (Cornell University)
Recommender systems (RS) are pivotal in managing information overload in modern digital services. A key challenge in RS is efficiently processing vast item pools to deliver highly personalized recommendations under strict latency constraints. Multi-stage cascade …
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Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
2019
User response prediction, which models the user preference w.r.t. the presented items, plays a key role in online services. With two-decade rapid development, nowadays the cumulated user behavior sequences on mature Internet service platforms have …
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User Behavior Retrieval for Click-Through Rate Prediction
2020
Click-through rate (CTR) prediction plays a key role in modern online personalization services. In practice, it is necessary to capture user's drifting interests by modeling sequential user behaviors to build an accurate CTR prediction model. …
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An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph
2020
There is an influx of heterogeneous information network (HIN) based recommender systems in recent years since HIN is capable of characterizing complex graphs and contains rich semantics. Although the existing approaches have achieved performance improvement, …