476 citations · 930 across the 34 of their papers we have counts for
8 papers · 1 filter
Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social Networks
Taotao Cai, Shuiqiao Yang, Jianxin Li +5
User engagement has recently received significant attention in understanding the decay and expansion of communities in many online social networking platforms. When a user chooses…
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
Hao Peng, Jianxin Li, Yangqiu Song +4
Events are happening in real-world and real-time, which can be planned and organized for occasions, such as social gatherings, festival celebrations, influential meetings or sports…
Dynamic Network Embedding Survey
Guotong Xue, Ming Zhong, Jianxin Li +3
Since many real world networks are evolving over time, such as social networks and user-item networks, there are increasing research efforts on dynamic network embedding in recent…
Top-k Socio-Spatial Co-engaged Location Selection for Social Users
Nur Al Hasan Haldar, Jianxin Li, Mohammed Eunus Ali +3
With the advent of location-based social networks, users can tag their daily activities in different locations through check-ins. These check-in locations signify user preferences…
MODEL: Motif-based Deep Feature Learning for Link Prediction
Lei Wang, Jing Ren, Bo Xu +3
Link prediction plays an important role in network analysis and applications. Recently, approaches for link prediction have evolved from traditional similarity-based algorithms int…
Adversarial Directed Graph Embedding
Shijie Zhu, Jianxin Li, Hao Peng +2
Node representation learning for directed graphs is critically important to facilitate many graph mining tasks. To capture the directed edges between nodes, existing methods mostly…
Heuristic Semi-Supervised Learning for Graph Generation Inspired by Electoral College
Chen Li, Xutan Peng, Hao Peng +4
Recently, graph-based algorithms have drawn much attention because of their impressive success in semi-supervised setups. For better model performance, previous studies learn to tr…
Inferring Multiplex Diffusion Network via Multivariate Marked Hawkes Process
Peiyuan Suny, Jianxin Li, Yongyi Mao +2
Understanding the diffusion in social network is an important task. However, this task is challenging since (1) the network structure is usually hidden with only observations of ev…