Reinforcement learning based meta-path discovery in large-scale heterogeneous information networks
Meta-paths are important tools for a wide variety of data mining and network analysis tasks
in Heterogeneous Information Networks (HINs), due to their flexibility and interpretability to …
in Heterogeneous Information Networks (HINs), due to their flexibility and interpretability to …
Mutual information model for link prediction in heterogeneous complex networks
Recently, a number of meta-path based similarity indices like PathSim, HeteSim, and
random walk have been proposed for link prediction in heterogeneous complex networks …
random walk have been proposed for link prediction in heterogeneous complex networks …
Automatic meta-path discovery for effective graph-based recommendation
Heterogeneous Information Networks (HINs) are labeled graphs that depict relationships
among different types of entities (eg, users, movies and directors). For HINs, meta-path …
among different types of entities (eg, users, movies and directors). For HINs, meta-path …
Meta-Path Learning for Multi-relational Graph Neural Networks
Existing multi-relational graph neural networks use one of two strategies for identifying
informative relations: either they reduce this problem to low-level weight learning, or they …
informative relations: either they reduce this problem to low-level weight learning, or they …
A multilayered approach for link prediction in heterogeneous complex networks
Link prediction problem is a difficult task in complex networks due to (i) network size and
sparsity, and (ii) extracting efficient similarity measures between node pairs. Although many …
sparsity, and (ii) extracting efficient similarity measures between node pairs. Although many …
Multi-kernel one class link prediction in heterogeneous complex networks
The heterogeneity of a network causes major challenges for link prediction in
heterogeneous complex networks. To deal with this problem, supervised link prediction …
heterogeneous complex networks. To deal with this problem, supervised link prediction …
Evaluating top-k meta path queries on large heterogeneous information networks
Heterogeneous information networks (HINs), which are typed graphs with labeled nodes
and edges, have attracted tremendous interest from academia and industry. Given two HIN …
and edges, have attracted tremendous interest from academia and industry. Given two HIN …
Reinforced meta-path selection for recommendation on heterogeneous information networks
Abstract Heterogeneous Information Networks (HINs) capture complex relations among
entities of various kinds and have been used extensively to improve the effectiveness of …
entities of various kinds and have been used extensively to improve the effectiveness of …
MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks
Heterogeneous Information Network (HIN) is essential to study complicated networks
containing multiple edge types and node types. Meta-path, a sequence of node types and …
containing multiple edge types and node types. Meta-path, a sequence of node types and …
LLM4HIN: Discovering Meta-path with Large Language Model for Reasoning on Complex Heterogeneous Information Networks
H Cheng, S Liu, C Fan, K Huang, H He… - … on Internet of Things …, 2024 - ieeexplore.ieee.org
Heterogeneous Information Networks (HINs) are complex structures hosting various types of
entity nodes and diverse relationships. Meta-paths are crucial in HINs for relaying detailed …
entity nodes and diverse relationships. Meta-paths are crucial in HINs for relaying detailed …