MulEA: Multi-type Entity Alignment of Heterogeneous Medical Knowledge Graphs

Mingxia Wang; Peng Tian; Yun Xiong; Jingwen Yue; Yao Zhang; Chunlei Tang

doi:10.1007/978-3-031-30672-3_49

ScienceGate Book Chapters

BOOK-CHAPTER

MulEA: Multi-type Entity Alignment of Heterogeneous Medical Knowledge Graphs

Mingxia Wang Peng Tian Yun Xiong Jingwen Yue Yao Zhang Chunlei Tang

Year: 2023 Lecture notes in computer science Pages: 732-741 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-30672-3_49

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Knowledge graph Medical knowledge Embedding Graph Redundancy (engineering) Theoretical computer science Artificial intelligence Data mining

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.10

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

Data Quality and Management

Social Sciences → Decision Sciences → Management Science and Operations Research

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

MulEA: Multi-type Entity Alignment of Heterogeneous Medical Knowledge Graphs

Metrics

Topics

Related Documents

Collective Multi-type Entity Alignment Between Knowledge Graphs

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

Entity Alignment Between Knowledge Graphs Using Entity Type Matching

Towards Unsupervised Entity Alignment for Highly Heterogeneous Knowledge Graphs

Multi-heterogeneous neighborhood-aware for Knowledge Graphs alignment