activity
20182022
most citedMulti-Interest Network with Dynamic Routing for Recommendation at Tmall

51 citations · 102 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2022

Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and Clustering

Jun Gao, Wei Wang, Changlong Yu +3

Representations of events described in text are important for various tasks. In this work, we present SWCC: a Simultaneous Weakly supervised Contrastive learning and Clustering fra…

cs.LG20207 cited

Simplifying Architecture Search for Graph Neural Network

Huan Zhao, Lanning Wei, Quanming Yao

Recent years have witnessed the popularity of Graph Neural Networks (GNN) in various scenarios. To obtain optimal data-specific GNN architectures, researchers turn to neural archit…

cs.SI2020

Vertex-reinforced Random Walk for Network Embedding

Wenyi Xiao, Huan Zhao, Vincent W. Zheng +1

In this paper, we study the fundamental problem of random walk for network embedding. We propose to use non-Markovian random walk, variants of vertex-reinforced random walk (VRRW),…

cs.SI2019

Ranking Users in Social Networks with Motif-based PageRank

Huan Zhao, Xiaogang Xu, Yangqiu Song +3

PageRank has been widely used to measure the authority or the influence of a user in social networks. However, conventional PageRank only makes use of edge-based relations, which r…

cs.SI2019

Motif Enhanced Recommendation over Heterogeneous Information Network

Huan Zhao, Yingqi Zhou, Yangqiu Song +1

Heterogeneous Information Networks (HIN) has been widely used in recommender systems (RSs). In previous HIN-based RSs, meta-path is used to compute the similarity between users and…

cs.IR20199 cited

Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction

Wenyi Xiao, Huan Zhao, Haojie Pan +3

An effective content recommendation in modern social media platforms should benefit both creators to bring genuine benefits to them and consumers to help them get really interestin…