Papers Entity Alignment
“Entity Alignment” 태그가 달린 논문 211편 · 필터 해제
RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment
Entity alignment (EA) is the task to discover entities referring to the same real-world object from different knowledge graphs (KGs), which is the most crucial step in integrating multi-source KGs. The majority of the ex…
Entity AlignmentGraph AttentionKnowledge GraphsRelationWider Vision: Enriching Convolutional Neural Networks via Alignment to External Knowledge Bases
Deep learning models suffer from opaqueness. For Convolutional Neural Networks (CNNs), current research strategies for explaining models focus on the target classes within the associated training dataset. As a result, th…
Entity AlignmentExplainable ModelsZero-Shot LearningTowards Entity Alignment in the Open World: An Unsupervised Approach
Entity alignment (EA) aims to discover the equivalent entities in different knowledge graphs (KGs). It is a pivotal step for integrating KGs to increase knowledge coverage and quality. Recent years have witnessed a rapid…
Entity AlignmentKnowledge GraphsCross-Lingual Named Entity Recognition Using Parallel Corpus: A New Approach Using XLM-RoBERTa Alignment
We propose a novel approach for cross-lingual Named Entity Recognition (NER) zero-shot transfer using parallel corpora. We built an entity alignment model on top of XLM-RoBERTa to project the entities detected on the Eng…
Cross-Lingual NEREntity Alignmentnamed-entity-recognitionNamed Entity Recognition+3Reinforcement Learning based Collective Entity Alignment with Adaptive Features
Entity alignment (EA) is the task of identifying the entities that refer to the same real-world object but are located in different knowledge graphs (KGs). For entities to be aligned, existing EA solutions treat them sep…
Decision MakingEntity AlignmentKnowledge Graphsreinforcement-learning+2Towards Principled Representation Learning for Entity Alignment
Knowledge graph (KG) representation learning for entity alignment has recently received great attention. Compared with conventional methods, these embedding-based ones are considered to be robuster for highly-heterogeneo…
Entity AlignmentMachine TranslationRepresentation LearningRelation-Aware Neighborhood Matching Model for Entity Alignment
Entity alignment which aims at linking entities with the same meaning from different knowledge graphs (KGs) is a vital step for knowledge fusion. Existing research focused on learning embeddings of entities by utilizing …
Entity AlignmentKnowledge GraphsmodelRelationDual Attention Network for Cross-lingual Entity Alignment
Cross-lingual Entity alignment is an essential part of building a knowledge graph, which can help integrate knowledge among different language knowledge graphs. In the real KGs, there exists an imbalance among the inform…
Entity AlignmentGraph AttentionKnowledge GraphsRelationA Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment
Cross-lingual entity alignment, which aims to match equivalent entities in KGs with different languages, has attracted considerable focus in recent years. Recently, many graph neural network (GNN) based methods are propo…
Entity AlignmentGraph AttentionGraph Neural NetworkEntity Alignment for Knowledge Graphs with Multi-order Convolutional Networks
Knowledge graphs (KGs) have become popular structures for unifying real-world entities by modelling the relationships between them and their attributes. Entity alignment -- the task of identifying corresponding entities …
AttributeEntity AlignmentKnowledge GraphsA Critical Assessment of State-of-the-Art in Entity Alignment
In this work, we perform an extensive investigation of two state-of-the-art (SotA) methods for the task of Entity Alignment in Knowledge Graphs. Therefore, we first carefully examine the benchmarking process and identify…
BenchmarkingEntity AlignmentHyperparameter OptimizationKnowledge GraphsAn Industry Evaluation of Embedding-based Entity Alignment
Embedding-based entity alignment has been widely investigated in recent years, but most proposed methods still rely on an ideal supervised learning setting with a large number of unbiased seed mappings for training and v…
Entity AlignmentKnowledge GraphsDistributed Representations of Entities in Open-World Knowledge Graphs
Graph neural network (GNN)-based methods have demonstrated remarkable performance in various knowledge graph (KG) tasks. However, most existing approaches rely on observing all entities during training, posing a challeng…
Entity AlignmentGraph Neural NetworkGraph Representation LearningKnowledge Graphs+2Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment
Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of rich content by linking the equivalent entities from various KGs. GNN-based EA methods present promising performances by modeling the KG structure …
AttributeEntity AlignmentKnowledge Association with Hyperbolic Knowledge Graph Embeddings
Capturing associations for knowledge graphs (KGs) through entity alignment, entity type inference and other related tasks benefits NLP applications with comprehensive knowledge representations. Recent related methods bui…
Entity AlignmentGraph Neural NetworkKnowledge Graph EmbeddingsKnowledge GraphsVisual Pivoting for (Unsupervised) Entity Alignment
This work studies the use of visual semantic representations to align entities in heterogeneous knowledge graphs (KGs). Images are natural components of many existing KGs. By combining visual knowledge with other auxilia…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentMMEA: Entity Alignment for Multi-Modal Knowledge Graphs
Entity alignment plays an essential role in the knowledge graph (KG) integration. Though large efforts have been made on exploring the association of relational embeddings between different knowledge graphs, they may fai…
Entity AlignmentKnowledge GraphsMultimodal Deep LearningMulti-modal Entity AlignmentRelational Reflection Entity Alignment
Entity alignment aims to identify equivalent entity pairs from different Knowledge Graphs (KGs), which is essential in integrating multi-source KGs. Recently, with the introduction of GNNs into entity alignment, the arch…
Entity AlignmentKnowledge GraphsLink PredictionAlignNet: Unsupervised Entity Alignment
Recently developed deep learning models are able to learn to segment scenes into component objects without supervision. This opens many new and exciting avenues of research, allowing agents to take objects (or entities) …
Entity AlignmentDegree-Aware Alignment for Entities in Tail
Entity alignment (EA) is to discover equivalent entities in knowledge graphs (KGs), which bridges heterogeneous sources of information and facilitates the integration of knowledge. Existing EA solutions mainly rely on st…
Entity AlignmentKnowledge GraphsWord Embeddings