Mvtucker: Multi-view knowledge graphs representation learning based on tensor tucker model
Recently, more and more multi-view knowledge graphs with various important attributes are
being constructed and applied, such as temporal information, geolocation, commonsense …
being constructed and applied, such as temporal information, geolocation, commonsense …
A survey: knowledge graph entity alignment research based on graph embedding
B Zhu, R Wang, J Wang, F Shao, K Wang - Artificial Intelligence Review, 2024 - Springer
Entity alignment (EA) aims to automatically match entities in different knowledge graphs,
which is beneficial to the development of knowledge-driven applications. Representation …
which is beneficial to the development of knowledge-driven applications. Representation …
TS-align: A temporal similarity-aware entity alignment model for temporal knowledge graphs
Z Zhang, L Bai, L Zhu - Information Fusion, 2024 - Elsevier
Entity Alignment (EA) is a crucial step in knowledge graph fusion, aiming to match
equivalent entity pairs across different knowledge graphs (KGs). In recent years, Temporal …
equivalent entity pairs across different knowledge graphs (KGs). In recent years, Temporal …
Enabling inductive knowledge graph completion via structure-aware attention network
Abstract Knowledge graph completion (KGC) aims at complementing missing entities and
relations in a knowledge graph (KG). Popular KGC approaches based on KG embedding …
relations in a knowledge graph (KG). Popular KGC approaches based on KG embedding …
Open knowledge graph completion with negative-aware representation learning and multi-source reliability inference
Multi-source data fusion is essential for building smart cities by providing a comprehensive
and holistic understanding of urban environments. Specifically, smart city-oriented …
and holistic understanding of urban environments. Specifically, smart city-oriented …
An unsupervised multi-view contrastive learning framework with attention-based reranking strategy for entity alignment
Y Liang, W Cai, M Yang, Y Jiang - Neural Networks, 2024 - Elsevier
Entity alignment is a crucial task in knowledge graphs, aiming to match corresponding
entities from different knowledge graphs. Due to the scarcity of pre-aligned entities in real …
entities from different knowledge graphs. Due to the scarcity of pre-aligned entities in real …
ConeE: Global and local context-enhanced embedding for inductive knowledge graph completion
Abstract Knowledge graph completion (KGC) aims at completing missing information in
knowledge graphs (KGs). Most previous works work well in the transductive setting, but are …
knowledge graphs (KGs). Most previous works work well in the transductive setting, but are …