Results 111 to 120 of about 8,119,426 (288)
Knowledge Graph Completion Algorithm with Multi-view Contrastive Learning [PDF]
Knowledge graph completion is a process of reasoning new triples based on existing entities and relations in knowledge graph. The existing methods usually use the encoder-decoder framework.
QIAO Zifeng, QIN Hongchao, HU Jingjing, LI Ronghua, WANG Guoren
doaj +1 more source
Objective Ambulatory care–sensitive conditions (ACSCs) serve as indicators of access, quality, and performance of the health system. This study aimed to determine rheumatoid arthritis (RA)‐specific ACSCs for use in the evaluation of care system access and quality.
Kara Irwin +7 more
wiley +1 more source
Few-Shot Knowledge Graph Completion Based on Selective Attention [PDF]
Most few-shot knowledge graph completion models have some problems, such as low ability to learn relation representation and rarely attaching importance to the relative location and interaction between query entity pair when the relation between entities
LIN Sui, LU Chaohai, JIANG Wenchao, LIN Xiaoshan, ZHOU Weilin
doaj +1 more source
A Pre-training Framework for Knowledge Graph Completion
Knowledge graph completion (KGC) is one of the effective methods to identify new facts in knowledge graph. Except for a few methods based on graph network, most of KGC methods trend to be trained based on independent triples, while are difficult to take ...
Yu, Jian +5 more
core
Objective Our objective was to describe the social networks of Black individuals with rheumatic and musculoskeletal conditions and understand the clustering of health‐related behaviors to inform future community‐based, peer‐led interventions. Methods We used an adapted Personal Network Survey for Clinical Research (PERSNET) to map the personal social ...
Taussia Boadi +27 more
wiley +1 more source
Near‐surface deuterium enrichment profiles for different microstructural types of TiAl after exposure at 700 °C in a heavy water‐containing environment. The deuterium levels are significantly higher than expected from natural occurrence, indicating that the heavy water dissociated during the exposure treatment and entered the specimens.
Jonathan D. H. Paul +5 more
wiley +1 more source
A Brief Survey on Deep Learning-Based Temporal Knowledge Graph Completion
Temporal knowledge graph completion (TKGC) is the task of inferring missing facts based on existing ones in a temporal knowledge graph. In recent years, various TKGC methods have emerged, among which deep learning-based methods have achieved state-of-the-
Ningning Jia, Cuiyou Yao
doaj +1 more source
Bio‐Inspired Artificial Ionic Mechanoreceptor
A skin‐inspired artificial mechanoreceptor based on ionic interactions is presented for biomimetic tactile sensing. Pressure‐driven ionic redistribution within microfluidic channels generates a self‐powered electrical signal without external bias. The generated waveform exhibits mechanoreceptor‐like temporal features, including overshoot and undershoot,
Mohammad Akbari +4 more
wiley +1 more source
Knowledge Graph Completion Method Fusing Entity Descriptions and Topological Structure [PDF]
Knowledge graph completion aims to predict missing entities and relationships in given triplets to enhance the completeness and quality of the knowledge graph.Existing knowledge graph completion methods typically only consider the structural information ...
HAN Daojun, LI Yunsong, ZHANG Juntao, WANG Zemin
doaj +1 more source
Hierarchical Perceptual Graph Attention Network for Knowledge Graph Completion
Knowledge graph completion (KGC), the process of predicting missing knowledge through known triples, is a primary focus of research in the field of knowledge graphs.
Jianhao Zhang +3 more
core +1 more source

