Results 91 to 100 of about 175,928 (162)

A Relation-Specific Entropy-Based Ensemble Approach for Knowledge Graph Embedding

IEEE Access
Knowledge Graph Embedding (KGE) aims to represent entities and relationships from knowledge graphs (KGs) in vector spaces. Existing KGE methods often focus narrowly on specific relation patterns or employ ensemble weights based on the prediction scores ...
Hwawoo Jeon, Yoonseob Lim, Yong Suk Choi
doaj   +1 more source

Marie and BERT-A Knowledge Graph Embedding Based Question Answering System for Chemistry. [PDF]

ACS Omega, 2023
Zhou X, Zhang S, Agarwal M, Akroyd J, Mosbach S, Kraft M.   +5 more
europepmc   +1 more source

Towards leveraging explicit negative statements in knowledge graph embeddings

Web Semantics
Knowledge Graphs are used in various domains to represent knowledge about entities and their relations. In the vast majority of cases, they capture what is known to be true about those entities, i.e., positive statements, while the Open World Assumption ...
Rita T. Sousa, Catia Pesquita, Heiko Paulheim   +2 more
doaj   +1 more source

Assessing the effects of hyperparameters on knowledge graph embedding quality. [PDF]

J Big Data, 2023
Lloyd O, Liu Y, R Gaunt T.
europepmc   +1 more source

Convolutional Models with Multi-Feature Fusion for Effective Link Prediction in Knowledge Graph Embedding. [PDF]

Entropy (Basel), 2023
Guo Q, Liao Y, Li Z, Lin H, Liang S.
europepmc   +1 more source

Location-Sensitive Embedding for Knowledge Graph Embedding [PDF]

Journal of Computer-Aided Design & Computer Graphics, 2021
Siheng Zhang, Wensheng Zhang
openaire   +1 more source

Knowledge Graph Completion Using Embeddings

, 2023
These slides summarize the current research conducted on Knowledge Graph Completion using Embeddings which was presented at Knowledge Graph Conference 2023.
openaire   +1 more source

Knowledge Graph Embedding for Hierarchical Entities Based on Auto-Embedding Size

Mathematics
Knowledge graph embedding represents entities and relations as low-dimensional continuous vectors. Recently, researchers have attempted to leverage the potential semantic connections between entities with hierarchical relationships in the knowledge graph.
Pengfei Zhang, Xiaoxue Zhang, Yang Fang, Jinzhi Liao, Wubin Ma, Zhen Tan, Weidong Xiao   +6 more
doaj   +1 more source

Advancing drug-target interaction prediction: a comprehensive graph-based approach integrating knowledge graph embedding and ProtBert pretraining. [PDF]

BMC Bioinformatics, 2023
Djeddi WE, Hermi K, Ben Yahia S, Diallo G.   +3 more
europepmc   +1 more source

Knowledge graph embedding for profiling the interaction between transcription factors and their target genes. [PDF]

PLoS Comput Biol, 2023
Wu YH, Huang YA, Li JQ, You ZH, Hu PW, Hu L, Leung VCM, Du ZH.   +7 more
europepmc   +1 more source