SybilFlyover: Heterogeneous graph-based fake account detection model on social networks
S Li, J Yang, G Liang, T Li, K Zhao - Knowledge-Based Systems, 2022 - Elsevier
Organized social robot accounts can launch Sybil attacks on online social networks (OSNs)
for various malicious purposes, thus significantly affecting the user experience of online …
for various malicious purposes, thus significantly affecting the user experience of online …
Review of heterogeneous graph embedding methods based on deep learning techniques and comparing their efficiency in node classification
Graph embedding is an advantageous technique for reducing computational costs and
effectively using graph information in machine learning tasks like classification, clustering …
effectively using graph information in machine learning tasks like classification, clustering …
High-order proximity and relation analysis for cross-network heterogeneous node classification
Cross-network node classification aims to leverage the labeled nodes from a source network
to assist the learning in a target network. Existing approaches work mainly in homogeneous …
to assist the learning in a target network. Existing approaches work mainly in homogeneous …
RIECN: learning relation-based interactive embedding convolutional network for knowledge graph
Most knowledge graphs (KGs) are large and incomplete graph-structure database, which
can be completed by predicting miss links according to the existing knowledge. The …
can be completed by predicting miss links according to the existing knowledge. The …
Meta-path-based key node identification in heterogeneous networks
P Wang, J Shu, L Liu, X Yao - Frontiers in Physics, 2024 - frontiersin.org
Identifying key nodes in complex networks remains challenging. Whereas previous studies
focused on homogeneous networks, real-world systems comprise multiple node and edge …
focused on homogeneous networks, real-world systems comprise multiple node and edge …