output
20062026
most citedThe Medical Segmentation Decathlon

1.3k citations

Showing 2019 · cs.SIShow all

7 papers · 2 filters

cs.SI2019★ 2 cited

Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries

Sibo Wang, Renchi Yang, Runhui Wang +5

Given a graph , a source node and a target node , the personalized PageRank (PPR) of with respect to is the probability that a random walk starting from termi…

cs.SI2019★ 5 cited

A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models

Heng Chang, Yu Rong, Tingyang Xu +5

With the great success of graph embedding model on both academic and industry area, the robustness of graph embedding against adversarial attack inevitably becomes a central proble…

cs.SI2019★ 38 cited

Intelligent social bots uncover the link between user preference and diversity of news consumption

Yong Min, Tingjun Jiang, Cheng Jin +2

The boom of online social media and microblogging platforms has rapidly alter the way we consume news and exchange opinions. Even though considerable efforts try to recommend vario…

cs.SI2019★ 12 cited

Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks

Hao Peng, Jianxin Li, Qiran Gong +4

Events are happening in real-world and real-time, which can be planned and organized occasions involving multiple people and objects. Social media platforms publish a lot of text m…

cs.SI2019★ 9 cited

Popularity Prediction on Social Platforms with Coupled Graph Neural Networks

Qi Cao, Huawei Shen, Jinhua Gao +2

Predicting the popularity of online content on social platforms is an important task for both researchers and practitioners. Previous methods mainly leverage demographics, temporal…

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…