Papers Entity Alignment
“Entity Alignment” 태그가 달린 논문 211편 · 필터 해제
From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment
Entity Alignment (EA) aims to find the equivalent entities between two Knowledge Graphs (KGs). Existing methods usually encode the triples of entities as embeddings and learn to align the embeddings, which prevents the d…
AttributeEntity AlignmentKnowledge GraphsLanguage Modeling+2A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment
Entity alignment is the task of identifying corresponding entities across different knowledge graphs (KGs). Although recent embedding-based entity alignment methods have shown significant advancements, they still struggl…
Entity AlignmentKnowledge GraphsGeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark
With a fast developing pace of geographic applications, automatable and intelligent models are essential to be designed to handle the large volume of information. However, few researchers focus on geographic natural lang…
Entity AlignmentNatural Language UnderstandingType-enhanced Ensemble Triple Representation via Triple-aware Attention for Cross-lingual Entity Alignment
Entity alignment(EA) is a crucial task for integrating cross-lingual and cross-domain knowledge graphs(KGs), which aims to discover entities referring to the same real-world object from different KGs. Most existing metho…
DiversityEntity AlignmentKnowledge GraphsSpecificityOTIEA:Ontology-enhanced Triple Intrinsic-Correlation for Cross-lingual Entity Alignment
Cross-lingual and cross-domain knowledge alignment without sufficient external resources is a fundamental and crucial task for fusing irregular data. As the element-wise fusion process aiming to discover equivalent objec…
DecoderEntity AlignmentKnowledge GraphsImproving Knowledge Graph Entity Alignment with Graph Augmentation
Entity alignment (EA) which links equivalent entities across different knowledge graphs (KGs) plays a crucial role in knowledge fusion. In recent years, graph neural networks (GNNs) have been successfully applied in many…
Entity AlignmentKnowledge GraphsRelationRepresentation LearningSEA: A Scalable Entity Alignment System
Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). State-of-the-art EA approaches generally use Graph Neural Networks (GNNs) to encode entities. However, most of them train the mo…
Entity AlignmentGPUKnowledge GraphsInvestigating Graph Structure Information for Entity Alignment with Dangling Cases
Entity alignment (EA) aims to discover the equivalent entities in different knowledge graphs (KGs), which play an important role in knowledge engineering. Recently, EA with dangling entities has been proposed as a more r…
Contrastive LearningEntity AlignmentGraph AttentionKnowledge Graphs+1Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets
The flourishing of knowledge graph applications has driven the need for entity alignment (EA) across KGs. However, the heterogeneity of practical KGs, characterized by differing scales, structures, and limited overlappin…
Entity AlignmentKnowledge GraphsNavigateAttribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment
The multi-modal entity alignment (MMEA) aims to find all equivalent entity pairs between multi-modal knowledge graphs (MMKGs). Rich attributes and neighboring entities are valuable for the alignment task, but existing wo…
AttributeEntity AlignmentGraph Neural NetworkGraph Representation Learning+4VTQA: Visual Text Question Answering via Entity Alignment and Cross-Media Reasoning
The ideal form of Visual Question Answering requires understanding, grounding and reasoning in the joint space of vision and language and serves as a proxy for the AI task of scene understanding. However, most existing V…
Answer GenerationEntity AlignmentQuestion AnsweringScene Understanding+2Vision, Deduction and Alignment: An Empirical Study on Multi-modal Knowledge Graph Alignment
Entity alignment (EA) for knowledge graphs (KGs) plays a critical role in knowledge engineering. Existing EA methods mostly focus on utilizing the graph structures and entity attributes (including literals), but ignore i…
Entity AlignmentKnowledge GraphsMulti-modal Knowledge GraphUnsupervised Entity Alignment for Temporal Knowledge Graphs
Entity alignment (EA) is a fundamental data integration task that identifies equivalent entities between different knowledge graphs (KGs). Temporal Knowledge graphs (TKGs) extend traditional knowledge graphs by introduci…
Data IntegrationDecoderEntity AlignmentGraph Matching+1MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
Multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) whose entities are associated with relevant images. However, current MMEA algorithms rely on KG-level modali…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentDependency-aware Self-training for Entity Alignment
Entity Alignment (EA), which aims to detect entity mappings (i.e. equivalent entity pairs) in different Knowledge Graphs (KGs), is critical for KG fusion. Neural EA methods dominate current EA research but still suffer f…
Entity AlignmentKnowledge GraphsGuiding Neural Entity Alignment with Compatibility
Entity Alignment (EA) aims to find equivalent entities between two Knowledge Graphs (KGs). While numerous neural EA models have been devised, they are mainly learned using labelled data only. In this work, we argue that …
Entity AlignmentKnowledge GraphsEventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been drawing a lot of attention recently becau…
AttributeBenchmarkingEntity AlignmentKnowledge GraphsAdapters for Enhanced Modeling of Multilingual Knowledge and Text
Large language models appear to learn facts from the large text corpora they are trained on. Such facts are encoded implicitly within their many parameters, making it difficult to verify or manipulate what knowledge has …
Entity AlignmentKnowledge Graph CompletionKnowledge GraphsLightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation
Entity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core step of bridging and integrating multi-source KGs. In this paper, we argue that existing GNN-based EA methods inherit the inborn d…
Entity AlignmentTransAlign: Fully Automatic and Effective Entity Alignment for Knowledge Graphs
The task of entity alignment between knowledge graphs (KGs) aims to identify every pair of entities from two different KGs that represent the same entity. Many machine learning-based methods have been proposed for this t…
Entity AlignmentEntity EmbeddingsKnowledge Graphs