402 citations
- Zhejiang UniversityCN32 papers
- Alibaba Group (China)CN17 papers
- Peking UniversityCN13 papers
- Bellevue Hospital CenterUS12 papers
- Chinese Academy of SciencesCN10 papers
- Nanyang Technological UniversitySG10 papers
- Tsinghua UniversityCN8 papers
- Renmin University of ChinaCN7 papers
- Tianjin UniversityCN7 papers
- East China Normal UniversityCN6 papers
- Shanghai Jiao Tong UniversityCN6 papers
- University of Hong KongHK6 papers
11 papers · 1 filter
Dynamic Sequential Graph Learning for Click-Through Rate Prediction
Yunfei Chu, Xiaofu Chang, Kunyang Jia +2
Click-through rate prediction plays an important role in the field of recommender system and many other applications. Existing methods mainly extract user interests from user histo…
LHRM: A LBS based Heterogeneous Relations Model for User Cold Start Recommendation in Online Travel Platform
Ziyi Wang, Wendong Xiao, Yu Li +2
Most current recommender systems used the historical behaviour data of user to predict user' preference. However, it is difficult to recommend items to new users accurately. To all…
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
Yang Deng, Yaliang Li, Fei Sun +2
Conversational recommender systems (CRS) enable the traditional recommender systems to explicitly acquire user preferences towards items and attributes through interactive conversa…
Explore User Neighborhood for Real-time E-commerce Recommendation
Xu Xie, Fei Sun, Xiaoyong Yang +4
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been wid…
Learning a Product Relevance Model from Click-Through Data in E-Commerce
Shaowei Yao, Jiwei Tan, Xi Chen +4
The search engine plays a fundamental role in online e-commerce systems, to help users find the products they want from the massive product collections. Relevance is an essential r…
ICS-Assist: Intelligent Customer Inquiry Resolution Recommendation in Online Customer Service for Large E-Commerce Businesses
Min Fu, Jiwei Guan, Xi Zheng +6
Efficient and appropriate online customer service is essential to large e-commerce businesses. Existing solution recommendation methods for online customer service are unable to de…