Supervised ranking framework for relationship prediction in heterogeneous information networks
In recent years, relationship prediction in heterogeneous information networks (HINs) has
become an active topic. The most essential part of this task is how to effectively represent …
become an active topic. The most essential part of this task is how to effectively represent …
S-rank: a supervised ranking framework for relationship prediction in heterogeneous information networks
W Liang, X He, D Tang, X Zhang - International Conference on Industrial …, 2016 - Springer
The most crucial part for relationship prediction in heterogeneous information networks
(HIN) is how to effectively represent and utilize the information hidden in the creation of …
(HIN) is how to effectively represent and utilize the information hidden in the creation of …
A unified link prediction framework for predicting arbitrary relations in heterogeneous academic networks
M Lu, X Wei, D Ye, Y Dai - IEEE Access, 2019 - ieeexplore.ieee.org
Most of the existing link prediction methods for heterogeneous academic networks can only
predict one or two specific relation types rather than arbitrary relation types. Although …
predict one or two specific relation types rather than arbitrary relation types. Although …
Relation prediction via graph neural network in heterogeneous information networks with missing type information
Relation prediction is a fundamental task in network analysis which aims to predict the
relationship between two nodes. Thus, this differes from the traditional link prediction …
relationship between two nodes. Thus, this differes from the traditional link prediction …
Link prediction for heterogeneous information networks based on enhanced meta-path aggregation and attention mechanism
H Shao, L Wang, R Zhu - International Journal of Machine Learning and …, 2023 - Springer
Heterogeneous link prediction aims to reveal potential connections between two nodes in
heterogeneous information networks. Most existing studies are based on meta-paths, but …
heterogeneous information networks. Most existing studies are based on meta-paths, but …
Enhancing Predictive Expert Method for Link Prediction in Heterogeneous Information Social Networks
Link prediction is a critical prerequisite and foundation task for social network security that
involves predicting the potential relationship between nodes within a network or graph …
involves predicting the potential relationship between nodes within a network or graph …
Utilizing adjacency of colleagues and type correlations for enhanced link prediction
Discoveries of new relationships in the network of objects have been required in various
applications such as social networks, DBLP bibliographic networks and biological networks …
applications such as social networks, DBLP bibliographic networks and biological networks …
W-MMP2Vec: topic-driven network embedding model for link prediction in content-based heterogeneous information network
Link prediction on heterogeneous information network (HIN) is considered as a challenge
problem due to the complexity and diversity in types of nodes and links. Currently, there are …
problem due to the complexity and diversity in types of nodes and links. Currently, there are …
Explainable link prediction based on multi-granularity relation-embedded representation
J Zheng, Q Li, J Liao, S Wang - Knowledge-Based Systems, 2021 - Elsevier
Existing link prediction methods focus on mining relations of nodes in terms of network
structure, ignoring rich attributes of nodes. In the micro-blog social networks, text contents …
structure, ignoring rich attributes of nodes. In the micro-blog social networks, text contents …
Meta-path-based link prediction in schema-rich heterogeneous information network
Recent years have witnessed the boom of heterogeneous information network (HIN), which
contains different types of nodes and relations. Complex structure and rich semantics are …
contains different types of nodes and relations. Complex structure and rich semantics are …