32 citations · 112 across the 17 of their papers we have counts for
5 papers · 2 filters
Attention Weighted Mixture of Experts with Contrastive Learning for Personalized Ranking in E-commerce
Juan Gong, Zhenlin Chen, Chaoyi Ma +7
Ranking model plays an essential role in e-commerce search and recommendation. An effective ranking model should give a personalized ranking list for each user according to the use…
Vague Preference Policy Learning for Conversational Recommendation
Gangyi Zhang, Chongming Gao, Wenqiang Lei +6
Conversational recommendation systems (CRS) commonly assume users have clear preferences, leading to potential over-filtering of relevant alternatives. However, users often exhibit…
JDsearch: A Personalized Product Search Dataset with Real Queries and Full Interactions
Jiongnan Liu, Zhicheng Dou, Guoyu Tang +1
Recently, personalized product search attracts great attention and many models have been proposed. To evaluate the effectiveness of these models, previous studies mainly utilize th…
A Multi-Granularity Matching Attention Network for Query Intent Classification in E-commerce Retrieval
Chunyuan Yuan, Yiming Qiu, Mingming Li +3
Query intent classification, which aims at assisting customers to find desired products, has become an essential component of the e-commerce search. Existing query intent classific…
Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search
Binbin Wang, Mingming Li, Zhixiong Zeng +5
Retrieving relevant items that match users' queries from billion-scale corpus forms the core of industrial e-commerce search systems, in which embedding-based retrieval (EBR) metho…