CORE: A knowledge graph entity type prediction method via complex space regression and embedding-Reference-Cited by-同舟云学术

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CORE: A knowledge graph entity type prediction method via complex space regression and embedding

Published:2022-05 Issue: Volume:157 Page:97-103
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Ge Xiou^ORCID,Wang Yun-Cheng,Wang Bin,Kuo C.C. Jay

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference32 articles.

1. Representation learning of knowledge graphs with hierarchical types;Xie,2016

2. Distributed representation learning for knowledge graphs with entity descriptions;Fan;Pattern Recognit. Lett.,2017

3. AutoETER: Automated entity type representation for knowledge graph embedding;Niu,2020

4. Embedding entities and relations for learning and inference in knowledge bases;Yang,2014

5. Complex embeddings for simple link prediction;Trouillon,2016

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1. GFedKG: GNN-based federated embedding model for knowledge graph completion;Knowledge-Based Systems;2024-10

2. Entity type inference based on path walking and inter-types relationships;Data & Knowledge Engineering;2024-09

3. AsyncET: Asynchronous Representation Learning for Knowledge Graph Entity Typing;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. Instance type completion in equipment knowledge graph based on translation model;International Journal of Modeling, Simulation, and Scientific Computing;2024-07-23

5. Fine-Grained Entity-Type Completion Based on Neighborhood-Attention and Cartesian–Polar Coordinates Mapping;International Journal of Software Engineering and Knowledge Engineering;2024-06-19

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