activity
20122023
most citedLearning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors

200 citations · 1.6k across the 79 of their papers we have counts for

collaborators
Showing cs.SIShow all

13 papers · 1 filter

cs.SI2020★ 1 cited

A Dynamic and Cooperative Tracking System for Crowdfunding

Kai Zhang, Hongke Zhao, Qi Liu +2

Crowdfunding is an emerging finance platform for creators to fund their efforts by soliciting relatively small contributions from a large number of individuals using the Internet.…

cs.SI2019★ 133 cited

MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

Hao Wang, Tong Xu, Qi Liu +5

Recently, the Network Representation Learning (NRL) techniques, which represent graph structure via low-dimension vectors to support social-oriented application, have attracted wid…

cs.SI2018★ 74 cited

A Hierarchical Attention Model for Social Contextual Image Recommendation

Le Wu, Lei Chen, Richang Hong +3

Image based social networks are among the most popular social networking services in recent years. With tremendous images uploaded everyday, understanding users' preferences on use…

cs.SI2018★ 3 cited

Tracking Top-K Influential Vertices in Dynamic Networks

Yu Yang, Zhefeng Wang, Tianyuan Jin +2

Influence propagation in networks has enjoyed fruitful applications and has been extensively studied in literature. However, only very limited preliminary studies tackled the chall…

cs.SI2018★ 1 cited

Mining Density Contrast Subgraphs

Yu Yang, Lingyang Chu, Yanyan Zhang +3

Dense subgraph discovery is a key primitive in many graph mining applications, such as detecting communities in social networks and mining gene correlation from biological data. Mo…

cs.SI2018★ 7 cited

SPINE: Structural Identity Preserved Inductive Network Embedding

Junliang Guo, Linli Xu, Jingchang Liu

Recent advances in the field of network embedding have shown that low-dimensional network representation is playing a critical role in network analysis. Most existing network embed…

cs.SI2017★ 1 cited

Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective

Junliang Guo, Linli Xu, Xunpeng Huang +1

Recent advances in the field of network embedding have shown the low-dimensional network representation is playing a critical role in network analysis. However, most of the existin…

cs.SI2016★ 2 cited

Activity Maximization by Effective Information Diffusion in Social Networks

Zhefeng Wang, Yu Yang, Jian Pei +1

In a social network, even about the same information the excitements between different pairs of users are different. If you want to spread a piece of new information and maximize t…

cs.SI2016★ 3 cited

Predicting Social Status via Social Networks: A Case Study on University, Occupation, and Region

Hao Fu, Xing Xie, Yong Rui +3

Social status refers to the relative position within the society. It is an important notion in sociology and related research. The problem of measuring social status has been studi…

cs.SI2016★ 35 cited

Tracking Influential Nodes in Dynamic Networks

Yu Yang, Zhefeng Wang, Jian Pei +1

In this paper, we tackle a challenging problem inherent in a series of applications: tracking the influential nodes in dynamic networks. Specifically, we model a dynamic network as…

cs.SI2015

Information Coverage Maximization in Social Networks

Zhefeng Wang, Enhong Chen, Qi Liu +3

Social networks, due to their popularity, have been studied extensively these years. A rich body of these studies is related to influence maximization, which aims to select a set o…

cs.SI2012★ 1 cited

A Social Influence Model Based On Circuit Theory

Biao Xiang, Enhong Chen, Qi Liu +3

Understanding the behaviors of information propagation is essential for the effective exploitation of social influence in social networks. However, few existing influence models ar…

cs.SI2012

A Linear Circuit Model For Social Influence Analysis

Biao Xiang, Enhong Chen, Qi Liu +1

Understanding the behaviors of information propagation is essential for the effective exploitation of social influence in social networks. However, few existing influence models ar…