A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning
Abstract Knowledge Graph Embedding (KGE) has proven to be an effective approach to
solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to …
solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to …
Schema first! learn versatile knowledge graph embeddings by capturing semantics with maschine
Knowledge graph embedding models (KGEMs) have gained considerable traction in recent
years. These models learn a vector representation of knowledge graph entities and …
years. These models learn a vector representation of knowledge graph entities and …
KGDM: A Diffusion Model to Capture Multiple Relation Semantics for Knowledge Graph Embedding
Abstract Knowledge graph embedding (KGE) is an efficient and scalable method for
knowledge graph completion. However, most existing KGE methods suffer from the …
knowledge graph completion. However, most existing KGE methods suffer from the …
Modeling Knowledge Graphs with Composite Reasoning
W Cui, L Zhang - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
The ability to combine multiple pieces of existing knowledge to infer new knowledge is both
crucial and challenging. In this paper, we explore how facts of various entities are combined …
crucial and challenging. In this paper, we explore how facts of various entities are combined …
Fact Embedding through Diffusion Model for Knowledge Graph Completion
Knowledge graph embedding (KGE) is an efficient and scalable method for knowledge
graph completion tasks. Existing KGE models typically map entities and relations into a …
graph completion tasks. Existing KGE models typically map entities and relations into a …
[HTML][HTML] Conflict-aware multilingual knowledge graph completion
Abstract Knowledge graph completion (KGC), a task that aims at predicting missing links
with existing information inside a knowledge graph (KG), has emerged as a popular …
with existing information inside a knowledge graph (KG), has emerged as a popular …
KNOWFORMER: revisiting transformers for knowledge graph reasoning
Knowledge Completion Method Based on Relational Embedding with GNN
Y Chen, Z Yin, H Tan, X Lin - International Conference on Intelligent …, 2024 - Springer
Abstract Knowledge graph, as an effective representation of structured knowledge, plays an
increasingly important role in the field of artificial intelligence. However, the incompleteness …
increasingly important role in the field of artificial intelligence. However, the incompleteness …
Fact Embedding through Diffusion Model for Knowledge Graph Completion
L Zhuang, A Li, H Li, S Wang - The Web Conference 2024 - openreview.net
Knowledge graph embedding (KGE) is an efficient and scalable method for knowledge
graph completion tasks. Existing KGE models typically map entities and relations into a …
graph completion tasks. Existing KGE models typically map entities and relations into a …