IP屬地：上海
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Disentangled Graph Collaborative Filtering以下內(nèi)容純屬個(gè)人見(jiàn)解，歡迎大家交流衷掷。發(fā)布于2020 SIGIR 1 motivation 1.1 問(wèn)題 從交互數(shù)據(jù)中學(xué)習(xí)用戶和項(xiàng)目的信息表示對(duì)于...
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Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning以下內(nèi)容純屬個(gè)人見(jiàn)解，歡迎大家交流誊酌。發(fā)布于2021 SIGIR 1 motivation 1.1 問(wèn)題 CRS中三個(gè)決策問(wèn)題：詢問(wèn)哪些屬性、推薦...
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Learning to Ask Appropriate Questions in Conversational Recommendation以下內(nèi)容純屬個(gè)人見(jiàn)解露乏，歡迎大家交流碧浊。發(fā)布于2021 SIGIR 1 motivation 1.1 問(wèn)題 通過(guò)采用對(duì)話代理來(lái)動(dòng)態(tài)捕獲細(xì)粒度用戶偏好...
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Estimation–Action–Reflection: Towards Deep Interaction Between Conversational and Recommender Sys...以下內(nèi)容純屬個(gè)人見(jiàn)解，歡迎大家交流瘟仿。發(fā)布于2020 WSDM 1 motivation 1.1 問(wèn)題 推薦系統(tǒng)采用會(huì)話技術(shù)來(lái)動(dòng)態(tài)獲取用戶偏好箱锐，并...
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Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation以下內(nèi)容純屬個(gè)人見(jiàn)解，歡迎大家交流劳较。發(fā)布于2021 WSDM 1 motivation 1.1 問(wèn)題 現(xiàn)有的CRS用戶偏好模型通常將在線反饋信息...
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Self-Supervised Graph Transformer on Large-Scale Molecular Data以下內(nèi)容純屬個(gè)人見(jiàn)解驹止，歡迎大家交流。發(fā)布于2020 NIPS 1 motivation 如何獲取分子的信息表征是人工智能驅(qū)動(dòng)藥物設(shè)計(jì)和發(fā)現(xiàn)的重要...
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Graph Random Neural Networks for Semi-Supervised Learning on Graphs以下內(nèi)容純屬個(gè)人見(jiàn)解观蜗，歡迎大家交流臊恋。發(fā)布于2020 NIPS 1 motivation 1.1 問(wèn)題 1）當(dāng)前的GNN都容易o(hù)ver-smoot...
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DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Onl...以下內(nèi)容純屬個(gè)人見(jiàn)解，歡迎大家交流墓捻。發(fā)布于2019 ICDE 1 motivation 1.1 問(wèn)題 在線健康社區(qū)抖仅，如在線乳腺癌論壇，使患者(即...
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DREAM: A Dynamic Relational-Aware Model for Social Recommendation以下內(nèi)容純屬個(gè)人見(jiàn)解砖第，歡迎大家交流撤卢。發(fā)布于2020 CIKM短篇 1 motivation 1.1 問(wèn)題 社會(huì)關(guān)系在提高推薦系統(tǒng)的性能方面起著至...