MGDN: A Graph of Graphs Neural Network for Malware Detection
With the rapid evolution of software ecosystems, malware has become increasingly sophisticated, posing severe threats to cybersecurity. Modern malware often exhibits complex …
Finding critical users in social networks with reinforcement learning
Information Sciences, 2026
xulu-gong
SARL: A Scalable Attribute-Informed Representation Learning Framework for Bipartite Graphs
IEEE Transactions on Knowledge and Data Engineering, 2026
IGFM: An Enhanced Graph Similarity Computation Method with Fine-Grained Analysis
Abstract In the rapidly advancing field of graph-based applications, accurate graph similarity computing (GSC) has become increasingly important. However, due to the complexity of …
min-pei
Temporal Insights for Group-Based Fraud Detection on e-Commerce Platforms
Along with the rapid technological and commercial innovation on e-commerce platforms, an increasing number of frauds cause great harm to these platforms. Many frauds are conducted …
FPGN: follower prediction framework for infectious disease prevention
Abstract In recent years, how to prevent the widespread transmission of infectious diseases in communities has been a research hot spot. Tracing close contact with infected …
Neural Similarity Search on Supergraph Containment
Supergraph search is a fundamental graph query processing problem. Supergraph search aims to find all data graphs contained in a given query graph based on the subgraph …
hanchen-wang
Polarity-based graph neural network for sign prediction in signed bipartite graphs
Abstract As a fundamental data structure, graphs are ubiquitous in various applications. Among all types of graphs, signed bipartite graphs contain complex structures with positive …
xianhang-zhang
Bipartite graph capsule network
Abstract Graphs have been widely adopted in various fields, where many graph models are developed. Most of previous research focuses on unipartite or homogeneous graph analysis.
xianhang-zhang