EntityAlignment
Related Papers
Neighborhood Matching Network for Entity Alignment
AbstractStructural heterogeneity between knowledge graphs is an outstanding challenge for entity alignment. This paper presents Neighborhood Matching Network (NMN), a novel entity alignment framework for tackling the structural heterogeneity challenge. …...
Cross-lingual Entity Alignment with Incidental Supervision
AbstractMuch research effort has been put to multilingual knowledge graph (KG) embedding methods to address the entity alignment task, which seeks to match entities in different languagespecific KGs that refer …...
Global entity alignment with Gated Latent Space Neighborhood Aggregation
AbstractExisting entity alignment models mainly use the topology structure of the original knowledge graph and have achieved promising performance. However they are still challenged by the heterogeneous topological neighborhood structures …...
Knowing the No-match: Entity Alignment with Dangling Cases
AbstractThis paper studies a new problem setting of entity alignment for knowledge graphs (KGs). Since KGs possess different sets of entities, there could be entities that cannot find alignment across …...
Time-aware Graph Neural Network for Entity Alignment between Temporal Knowledge Graphs
AbstractEntity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information created the need for reasoning over …...
A Simple Temporal Information Matching Mechanism for Entity Alignment between Temporal Knowledge Graphs
AbstractEntity 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 …...
Deep Reinforcement Learning for Entity Alignment
AbstractEmbedding-based methods have attracted increasing attention in recent entity alignment (EA) studies. Although great promise they can offer, there are still several limitations. The most notable is that they identify …...
Guiding Neural Entity Alignment with Compatibility
AbstractEntity 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 …...
HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation
AbstractTables are often created with hierarchies, but existing works on table reasoning mainly focus on flat tables and neglect hierarchical tables. Hierarchical tables challenge numerical reasoning by complex hierarchical indexing, …...
Joint Completion and Alignment of Multilingual Knowledge Graphs
AbstractKnowledge Graph Completion (KGC) predicts missing facts in an incomplete Knowledge Graph (KG). Multilingual KGs associate entities and relations with surface forms written in different languages. An entity or relation …...
LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation
AbstractEntity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core step to bridging and integrating multi-source KGs. In this paper, we argue that existing complex …...