107 citations · 230 across the 6 of their papers we have counts for
6 papers
From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search
Rui Li, Yunjiang Jiang, Wenyun Yang +7
We introduce deep learning models to the two most important stages in product search at JD.com, one of the largest e-commerce platforms in the world. Specifically, we outline the d…
Off-policy Learning for Multiple Loggers
Li He, Long Xia, Wei Zeng +3
It is well known that the historical logs are used for evaluating and learning policies in interactive systems, e.g. recommendation, search, and online advertising. Since direct on…
Graph Neural Networks for Social Recommendation
Wenqi Fan, Yao Ma, Qing Li +4
In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph…
Product-Aware Answer Generation in E-Commerce Question-Answering
Shen Gao, Zhaochun Ren, Yihong Eric Zhao +3
In e-commerce portals, generating answers for product-related questions has become a crucial task. In this paper, we propose the task of product-aware answer generation, which tend…
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
Xisen Jin, Wenqiang Lei, Zhaochun Ren +4
The task of dialogue generation aims to automatically provide responses given previous utterances. Tracking dialogue states is an important ingredient in dialogue generation for es…
Deep Reinforcement Learning for List-wise Recommendations
Xiangyu Zhao, Liang Zhang, Long Xia +3
Recommender systems play a crucial role in mitigating the problem of information overload by suggesting users' personalized items or services. The vast majority of traditional reco…