Graph Percolation Embeddings for Efficient Knowledge Graph Inductive Reasoning

Kai Wang; Dan Lin; Siqiang Luo

doi:10.1109/tkde.2024.3508064

ScienceGate Book Chapters

JOURNAL ARTICLE

Graph Percolation Embeddings for Efficient Knowledge Graph Inductive Reasoning

Kai Wang Dan Lin Siqiang Luo

Year: 2024 Journal: IEEE Transactions on Knowledge and Data Engineering Vol: 37 (3)Pages: 1198-1212 Publisher: IEEE Computer Society

DOI: 10.1109/tkde.2024.3508064

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Theoretical computer science Graph Graph theory Mathematics Combinatorics

Metrics

Cited By

1.28

FWCI (Field Weighted Citation Impact)

Refs

0.79

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

Rough Sets and Fuzzy Logic

Physical Sciences → Computer Science → Computational Theory and Mathematics

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Graph Percolation Embeddings for Efficient Knowledge Graph Inductive Reasoning

Metrics

Citation History

Topics

Related Documents

Counterfactual Reasoning with Knowledge Graph Embeddings

Improving Knowledge Graph Embeddings with Ontological Reasoning

Query2Particles: Knowledge Graph Reasoning with Particle Embeddings

Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning

Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings