787 citations · 2.9k across the 66 of their papers we have counts for
11 papers · 1 filter
Learning Disentangled Representations for Recommendation
Jianxin Ma, Chang Zhou, Peng Cui +2
User behavior data in recommender systems are driven by the complex interactions of many latent factors behind the users' decision making processes. The factors are highly entangle…
Towards Knowledge-Based Recommender Dialog System
Qibin Chen, Junyang Lin, Yichang Zhang +4
In this paper, we propose a novel end-to-end framework called KBRD, which stands for Knowledge-Based Recommender Dialog System. It integrates the recommender system and the dialog…
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific Networks
Yuting Ye, Xuwu Wang, Jiangchao Yao +4
Low-dimensional embeddings of knowledge graphs and behavior graphs have proved remarkably powerful in varieties of tasks, from predicting unobserved edges between entities to conte…
Dimensional Reweighting Graph Convolutional Networks
Xu Zou, Qiuye Jia, Jianwei Zhang +3
Graph Convolution Networks (GCNs) are becoming more and more popular for learning node representations on graphs. Though there exist various developments on sampling and aggregatio…
Cognitive Knowledge Graph Reasoning for One-shot Relational Learning
Zhengxiao Du, Chang Zhou, Ming Ding +2
Inferring new facts from existing knowledge graphs (KG) with explainable reasoning processes is a significant problem and has received much attention recently. However, few studies…
Cognitive Graph for Multi-Hop Reading Comprehension at Scale
Ming Ding, Chang Zhou, Qibin Chen +2
We propose a new CogQA framework for multi-hop question answering in web-scale documents. Inspired by the dual process theory in cognitive science, the framework gradually builds a…