A survey on heterogeneous graph embedding: methods, techniques, applications and sources
Heterogeneous graphs (HGs) also known as heterogeneous information networks have
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
[HTML][HTML] A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources
As an important way to alleviate information overload, a recommender system aims to filter
out irrelevant information for users and provides them items that they may be interested in. In …
out irrelevant information for users and provides them items that they may be interested in. In …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
A survey on network embedding
Network embedding assigns nodes in a network to low-dimensional representations and
effectively preserves the network structure. Recently, a significant amount of progresses …
effectively preserves the network structure. Recently, a significant amount of progresses …
metapath2vec: Scalable representation learning for heterogeneous networks
We study the problem of representation learning in heterogeneous networks. Its unique
challenges come from the existence of multiple types of nodes and links, which limit the …
challenges come from the existence of multiple types of nodes and links, which limit the …
Meta-graph based recommendation fusion over heterogeneous information networks
Heterogeneous Information Network (HIN) is a natural and general representation of data in
modern large commercial recommender systems which involve heterogeneous types of …
modern large commercial recommender systems which involve heterogeneous types of …
Log2vec: A heterogeneous graph embedding based approach for detecting cyber threats within enterprise
F Liu, Y Wen, D Zhang, X Jiang, X **ng… - Proceedings of the 2019 …, 2019 - dl.acm.org
Conventional attacks of insider employees and emerging APT are both major threats for the
organizational information system. Existing detections mainly concentrate on users' behavior …
organizational information system. Existing detections mainly concentrate on users' behavior …
Effective and efficient community search over large heterogeneous information networks
Recently, the topic of community search (CS) has gained plenty of attention. Given a query
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …
HAGERec: Hierarchical attention graph convolutional network incorporating knowledge graph for explainable recommendation
Z Yang, S Dong - Knowledge-Based Systems, 2020 - Elsevier
Abstract Knowledge graph (KG) can provide auxiliary information for recommender system
to alleviate the sparsity and cold start problems, while graph convolutional networks (GCN) …
to alleviate the sparsity and cold start problems, while graph convolutional networks (GCN) …
A survey on heterogeneous network representation learning
Y **e, B Yu, S Lv, C Zhang, G Wang, M Gong - Pattern recognition, 2021 - Elsevier
Heterogeneous information networks usually contain different kinds of nodes and
distinguishing types of relations, which can preserve more information than homogeneous …
distinguishing types of relations, which can preserve more information than homogeneous …