Papers Entity Alignment
“Entity Alignment” 태그가 달린 논문 211편 · 필터 해제
Learning High-Quality and General-Purpose Phrase Representations
Phrase representations play an important role in data science and natural language processing, benefiting various tasks like Entity Alignment, Record Linkage, Fuzzy Joins, and Paraphrase Classification. The current state…
Contrastive LearningData AugmentationDiversityEntity AlignmentFedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion
Knowledge graph completion (KGC) aims to predict missing facts in knowledge graphs (KGs), which is crucial as modern KGs remain largely incomplete. While training KGC models on multiple aligned KGs can improve performanc…
Entity AlignmentFederated LearningKnowledge Graph CompletionKnowledge Graphs+4Generating Explanations to Understand and Repair Embedding-based Entity Alignment
Entity alignment (EA) seeks identical entities in different knowledge graphs, which is a long-standing task in the database research. Recent work leverages deep learning to embed entities in vector space and align them v…
Entity AlignmentKnowledge GraphsKnowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGs
Despite the recent popularity of knowledge graph (KG) related tasks and benchmarks such as KG embeddings, link prediction, entity alignment and evaluation of the reasoning abilities of pretrained language models as KGs, …
Entity AlignmentKnowledge GraphsLink PredictionMixTEA: Semi-supervised Entity Alignment with Mixture Teaching
Semi-supervised entity alignment (EA) is a practical and challenging task because of the lack of adequate labeled mappings as training data. Most works address this problem by generating pseudo mappings for unlabeled ent…
DiversityEntity AlignmentEntity Alignment Method of Science and Technology Patent based on Graph Convolution Network and Information Fusion
The entity alignment of science and technology patents aims to link the equivalent entities in the knowledge graph of different science and technology patent data sources. Most entity alignment methods only use graph neu…
AttributeEntity AlignmentGraph Neural NetworkMulti-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment
Multi-Modal Entity Alignment (MMEA) is a critical task that aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs). However, this task faces challenges due to the presence of different types…
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentMulti-modal Knowledge GraphUniversal Multi-modal Entity Alignment via Iteratively Fusing Modality Similarity Paths
The objective of Entity Alignment (EA) is to identify equivalent entity pairs from multiple Knowledge Graphs (KGs) and create a more comprehensive and unified KG. The majority of EA methods have primarily focused on the …
Entity AlignmentKnowledge GraphsMulti-modal Entity AlignmentKnow2BIO: A Comprehensive Dual-View Benchmark for Evolving Biomedical Knowledge Graphs
Knowledge graphs (KGs) have emerged as a powerful framework for representing and integrating complex biomedical information. However, assembling KGs from diverse sources remains a significant challenge in several aspects…
Data IntegrationEntity AlignmentKnowledge GraphsRepresentation LearningUnsupervised Deep Cross-Language Entity Alignment
Cross-lingual entity alignment is the task of finding the same semantic entities from different language knowledge graphs. In this paper, we propose a simple and novel unsupervised method for cross-language entity alignm…
Entity Alignmentfr-enKnowledge GraphsTwo is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions. To utilize multiple knowledge bases (KB), previous works merge all KBs into a single graph via entity alignment…
Entity AlignmentQuestion AnsweringRethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting associated visual information. However, exist…
BenchmarkingEntity AlignmentKnowledge Graph EmbeddingsKnowledge Graphs+1AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models
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 GraphsAn Effective and Efficient Time-aware Entity Alignment Framework via Two-aspect Three-view Label Propagation
Entity alignment (EA) aims to find the equivalent entity pairs between different knowledge graphs (KGs), which is crucial to promote knowledge fusion. With the wide use of temporal knowledge graphs (TKGs), time-aware EA …
Entity AlignmentKnowledge GraphsCombating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment
Entity alignment (EA) aims at identifying equivalent entity pairs across different knowledge graphs (KGs) that refer to the same real-world identity. To circumvent the shortage of seed alignments provided for training, r…
Entity AlignmentKnowledge GraphsPseudo LabelX-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents
Task-oriented dialogue research has mainly focused on a few popular languages like English and Chinese, due to the high dataset creation cost for a new language. To reduce the cost, we apply manual editing to automatical…
Entity AlignmentMachine TranslationTranslationCross-domain Recommender Systems via Multimodal Domain Adaptation
Collaborative Filtering (CF) has emerged as one of the most prominent implementation strategies for building recommender systems. The key idea is to exploit the usage patterns of individuals to generate personalized reco…
Collaborative FilteringDomain AdaptationEntity AlignmentRecommendation Systems+1What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings
Joint representation learning over multi-sourced knowledge graphs (KGs) yields transferable and expressive embeddings that improve downstream tasks. Entity alignment (EA) is a critical step in this process. Despite recen…
Entity AlignmentKnowledge Graph EmbeddingsKnowledge GraphsRepresentation LearningJoint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs
In this paper, we present the ``joint pre-training and local re-training'' framework for learning and applying multi-source knowledge graph (KG) embeddings. We are motivated by the fact that different KGs contain complem…
Entity AlignmentKnowledge DistillationKnowledge GraphsRepresentation Learning+1Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
Recent embedding-based methods have achieved great successes in exploiting entity alignment from knowledge graph (KG) embeddings of multiple modalities. In this paper, we study embedding-based entity alignment (EEA) from…
Entity AlignmentGenerative Adversarial Network