35 citations · 47 across the 9 of their papers we have counts for
9 papers
Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation
Likang Wu, Zhi Li, Hongke Zhao +5
Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.…
Finding Route Hotspots in Large Labeled Networks
Mingtao Lei, Xi Zhang, Lingyang Chu +3
In many advanced network analysis applications, like social networks, e-commerce, and network security, hotspots are generally considered as a group of vertices that are tightly co…
Mining Top-k Sequential Patterns in Database Graphs:A New Challenging Problem and a Sampling-based Approach
Mingtao Lei, Lingyang Chu, Zhefeng Wang
In many real world networks, a vertex is usually associated with a transaction database that comprehensively describes the behaviour of the vertex. A typical example is the social…
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…
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…
Finding Theme Communities from Database Networks
Lingyang Chu, Zhefeng Wang, Jian Pei +3
Given a database network where each vertex is associated with a transaction database, we are interested in finding theme communities. Here, a theme community is a cohesive subgraph…
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…
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…
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…