Papers Entity Alignment
“Entity Alignment” 태그가 달린 논문 211편 · 필터 해제
基于中文电子病历知识图谱的实体对齐研究(Research on Entity Alignment Based on Knowledge Graph of Chinese Electronic Medical Record)
“医疗知识图谱中知识重叠和互补的现象普遍存在,利用实体对齐进行医疗知识图谱融合成为迫切需要。然而据我们调研,目前医疗领域中的实体对齐尚没有一个完整的处理方案。因此本文提出了一个规范的基于中文电子病历的医疗知识图谱实体对齐流程,为医疗领域的实体对齐提供了一种可行的方案。同时针对基于中文电子病历医疗知识图谱之间结构异构性的特点,设计了一个双视角并行图神经网络丨乄乵乐乎乥乴丩模型用于解决医疗领域实体对齐,并取得较好的效果。”
Entity Alignment基于知识监督的标签降噪实体对齐(Refined De-noising for Labeled Entity Alignment from Auxiliary Evidence Knowledge)
“大多数现有的实体对齐解决方案都依赖于干净的标记数据来训练模型,很少关注种子噪声。为了解决实体对齐中的噪声问题,本文提出了一个标签降噪框架,在实体对齐中注入辅助知识和附带监督,以纠正标记和引导过程中的种子错误。特别是,考虑到以前基于邻域嵌入方法的弱点,本文应用了一种新的对偶关系注意力匹配编码器来加速知识图谱的结构学习,同时使用辅助知识来弥补结构表征的不足。然后,通过对抗训练来执行弱监督标签降噪。对于误差累积的问题,本文进一步使用对齐精化…
Entity AlignmentA Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs
Entity alignment (EA) aims to find entities in different knowledge graphs (KGs) that refer to the same object in the real world. Recent studies incorporate temporal information to augment the representations of KGs. The …
Entity AlignmentEntity EmbeddingsGraph Neural NetworkKnowledge GraphsEmbedding-Based Entity Alignment Using Relation Structural Similarity
Entity alignment aims to find entities in different knowledge graphs that semantically represent the same real-world entity. Recently, embedding-based entity alignment methods, which represent knowledge graphs as low-dim…
Entity AlignmentEntity EmbeddingsGraph EmbeddingKnowledge Graph Embedding+2Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment
Entity alignment aims to discover unique equivalent entity pairs with the same meaning across different knowledge graphs (KGs). Existing models have focused on projecting KGs into a latent embedding space so that inheren…
Entity AlignmentEntity EmbeddingsKnowledge GraphsPseudo LabelMulti-modal Contrastive Representation Learning for Entity Alignment
Multi-modal entity alignment aims to identify equivalent entities between two different multi-modal knowledge graphs, which consist of structural triples and images associated with entities. Most previous works focus on …
Contrastive LearningEntity AlignmentKnowledge GraphsMulti-modal Entity Alignment+1Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embedding
Entity alignment is a crucial task in knowledge graph fusion. However, most entity alignment approaches have the scalability problem. Recent methods address this issue by dividing large KGs into small blocks for embeddin…
Entity AlignmentHigh-quality Task Division for Large-scale Entity Alignment
Entity Alignment (EA) aims to match equivalent entities that refer to the same real-world objects and is a key step for Knowledge Graph (KG) fusion. Most neural EA models cannot be applied to large-scale real-life KGs du…
Entity AlignmentGPUInformativenessVocal Bursts Intensity PredictionMulti-modal Siamese Network for Entity Alignment
The booming of multi-modal knowledge graphs (MMKGs) has raised the imperative demand for multi-modal entity alignment techniques, which facilitate the integration of multiple MMKGs from separate data sources. Unfortunate…
AttributeContrastive LearningEntity AlignmentKnowledge Graphs+2$μ\text{KG}$: A Library for Multi-source Knowledge Graph Embeddings and Applications
This paper presents $\mu\text{KG}$, an open-source Python library for representation learning over knowledge graphs. $\mu\text{KG}$ supports joint representation learning over multi-source knowledge graphs (and also a si…
Entity AlignmentEntity TypingGPUGraph Embedding+7Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs
Entity alignment is a basic and vital technique in knowledge graph (KG) integration. Over the years, research on entity alignment has resided on the assumption that KGs are static, which neglects the nature of growth of …
Entity AlignmentInductive LearningKnowledge GraphsCybersecurity Entity Alignment via Masked Graph Attention Networks
Cybersecurity vulnerability information is often recorded by multiple channels, including government vulnerability repositories, individual-maintained vulnerability-gathering platforms, or vulnerability-disclosure email …
Entity AlignmentGraph AttentionEnriching Wikidata with Linked Open Data
Large public knowledge graphs, like Wikidata, contain billions of statements about tens of millions of entities, thus inspiring various use cases to exploit such knowledge graphs. However, practice shows that much of the…
Entity AlignmentKnowledge GraphsExploiting Global Semantic Similarities in Knowledge Graphs by Relational Prototype Entities
Knowledge graph (KG) embedding aims at learning the latent representations for entities and relations of a KG in continuous vector spaces. An empirical observation is that the head (tail) entities connected by the same r…
Entity AlignmentKnowledge GraphsRelationClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities
Entity alignment (EA) aims at finding equivalent entities in different knowledge graphs (KGs). Embedding-based approaches have dominated the EA task in recent years. Those methods face problems that come from the geometr…
Entity AlignmentEntity EmbeddingsKnowledge GraphsEntity Alignment with Reliable Path Reasoning and Relation-Aware Heterogeneous Graph Transformer
Entity Alignment (EA) has attracted widespread attention in both academia and industry, which aims to seek entities with same meanings from different Knowledge Graphs (KGs). There are substantial multi-step relation path…
Entity AlignmentKnowledge GraphsRelationEntity Alignment For Knowledge Graphs: Progress, Challenges, and Empirical Studies
Entity Alignment (EA) identifies entities across databases that refer to the same entity. Knowledge graph-based embedding methods have recently dominated EA techniques. Such methods map entities to a low-dimension space …
BenchmarkingEntity AlignmentKnowledge GraphsSubGraph Networks based Entity Alignment for Cross-lingual Knowledge Graph
Entity alignment is the task of finding entities representing the same real-world object in two knowledge graphs(KGs). Cross-lingual knowledge graph entity alignment aims to discover the cross-lingual links in the multi-…
Entity AlignmentKnowledge GraphsDangling-Aware Entity Alignment with Mixed High-Order Proximities
We study dangling-aware entity alignment in knowledge graphs (KGs), which is an underexplored but important problem. As different KGs are naturally constructed by different sets of entities, a KG commonly contains some d…
Entity AlignmentKnowledge GraphsVocal Bursts Intensity PredictionUniTranSeR: A Unified Transformer Semantic Representation Framework for Multimodal Task-Oriented Dialog System
As a more natural and intelligent interaction manner, multimodal task-oriented dialog system recently has received great attention and many remarkable progresses have been achieved. Nevertheless, almost all existing stud…
Entity Alignment