most citedRepresentation Learning for Attributed Multiplex Heterogeneous Network

479 citations · 575 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG201924 cited

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…

cs.CL201928 cited

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…

cs.IR201912 cited

Sequential Scenario-Specific Meta Learner for Online Recommendation

Zhengxiao Du, Xiaowei Wang, Hongxia Yang +2

Cold-start problems are long-standing challenges for practical recommendations. Most existing recommendation algorithms rely on extensive observed data and are brittle to recommend…

cs.SI201932 cited

Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

Ninghao Liu, Qiaoyu Tan, Yuening Li +3

Networks have been widely used as the data structure for abstracting real-world systems as well as organizing the relations among entities. Network embedding models are powerful to…

cs.SI2019479 cited

Representation Learning for Attributed Multiplex Heterogeneous Network

Yukuo Cen, Xu Zou, Jianwei Zhang +3

Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and ca…