Papers Temporal Knowledge Graph Completion
“Temporal Knowledge Graph Completion” 태그가 달린 논문 42편 · 필터 해제
TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion
Temporal knowledge graphs store the dynamics of entities and relations during a time period. However, typical temporal knowledge graphs often suffer from incomplete dynamics with missing facts in real-world scenarios. He…
Entity EmbeddingsKnowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionTemporal Knowledge Graph Reasoning with Low-rank and Model-agnostic Representations
Temporal knowledge graph completion (TKGC) has become a popular approach for reasoning over the event and temporal knowledge graphs, targeting the completion of knowledge with accurate but missing information. In this co…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+2ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations
Since conventional knowledge embedding models cannot take full advantage of the abundant textual information, there have been extensive research efforts in enhancing knowledge embedding using texts. However, existing enh…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+2RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Temporal factors are tied to the growth of facts in realistic applications, such as the progress of diseases and the development of political situation, therefore, research on Temporal Knowledge Graph (TKG) attracks much…
Knowledge Graph CompletionLink PredictionRelationRepresentation Learning+1Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion
Recent years, Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a Knowledge Graph (KG) into a geometric space and thus have gained incr…
Knowledge Graph CompletionKnowledge Graph EmbeddingsKnowledge GraphsLink Prediction+3Temporal Knowledge Graph Completion: A Survey
Knowledge graph completion (KGC) can predict missing links and is crucial for real-world knowledge graphs, which widely suffer from incompleteness. KGC methods assume a knowledge graph is static, but that may lead to ina…
Knowledge Graph CompletionKnowledge GraphsSurveyTemporal Knowledge Graph Completion+1A Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion
While knowledge graphs contain rich semantic knowledge about various entities and the relational information among them, temporal knowledge graphs (TKGs) describe and model the interactions of the entities over time. In …
Knowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionA Simple But Powerful Graph Encoder for Temporal Knowledge Graph Completion
Knowledge graphs contain rich knowledge about various entities and the relational information among them, while temporal knowledge graphs (TKGs) describe and model the interactions of the entities over time. In this cont…
Knowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionTime-dependent Entity Embedding is not All You Need: A Re-evaluation of Temporal Knowledge Graph Completion Models under a Unified Framework
Various temporal knowledge graph (KG) completion models have been proposed in the recent literature. The models usually contain two parts, a temporal embedding layer and a score function derived from existing static KG m…
AllEntity EmbeddingsGPUKnowledge Graph Completion+1TaCE: Time-aware Convolutional Embedding Learning for Temporal Knowledge Graph Completion
Temporal knowledge graph completion (TKGC) is a challenging task to infer the missing component for quadruples. The key challenge lies at how to integrate time information into the embeddings of entities and relations. R…
Knowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionTemporal Knowledge Graph Completion using Box Embeddings
Knowledge graph completion is the task of inferring missing facts based on existing data in a knowledge graph. Temporal knowledge graph completion (TKGC) is an extension of this task to temporal knowledge graphs, where e…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+1A Temporal Knowledge Graph Completion Method Based on Balanced Timestamp Distribution
Completion through the embedding representation of the knowledge graph (KGE) has been a research hotspot in recent years. Realistic knowledge graphs are mostly related to time, while most of the existing KGE algorithms i…
Knowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionTemporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings
Representation learning approaches for knowledge graphs have been mostly designed for static data. However, many knowledge graphs involve evolving data, e.g., the fact (The President of the United States is Barack Obama)…
Knowledge Graph CompletionKnowledge GraphsLink PredictionRepresentation Learning+2TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
Reasoning in a temporal knowledge graph (TKG) is a critical task for information retrieval and semantic search. It is particularly challenging when the TKG is updated frequently. The model has to adapt to changes in the …
Decision MakingInformation RetrievalKnowledge Graph CompletionRepresentation Learning+2T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion
Temporal knowledge graphs (TKGs) inherently reflect the transient nature of real-world knowledge, as opposed to static knowledge graphs. Naturally, automatic TKG completion has drawn much research interests for a more re…
DecoderKnowledge Graph CompletionKnowledge GraphsRelational Reasoning+2Tucker decomposition-based Temporal Knowledge Graph Completion
Knowledge graphs have been demonstrated to be an effective tool for numerous intelligent applications. However, a large amount of valuable knowledge still exists implicitly in the knowledge graphs. To enrich the existing…
Knowledge Graph CompletionKnowledge GraphsLink PredictionTemporal Knowledge Graph Completion+1DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion
There has recently been increasing interest in learning representations of temporal knowledge graphs (KGs), which record the dynamic relationships between entities over time. Temporal KGs often exhibit multiple simultane…
Knowledge Graph CompletionKnowledge GraphsRepresentation LearningTemporal Knowledge Graph CompletionTeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
Inferring missing facts in temporal knowledge graphs (TKGs) is a fundamental and challenging task. Previous works have approached this problem by augmenting methods for static knowledge graphs to leverage time-dependent …
ImputationKnowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionRTFE: A Recursive Temporal Fact Embedding Framework for Temporal Knowledge Graph Completion
Static knowledge graph (SKG) embedding (SKGE) has been studied intensively in the past years. Recently, temporal knowledge graph (TKG) embedding (TKGE) has emerged. In this paper, we propose a Recursive Temporal Fact Emb…
Graph EmbeddingKnowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionTemporal Knowledge Base Completion: New Algorithms and Evaluation Protocols
Temporal knowledge bases associate relational (s,r,o) triples with a set of times (or a single time instant) when the relation is valid. While time-agnostic KB completion (KBC) has witnessed significant research, tempora…
Knowledge Base CompletionKnowledge Graph CompletionKnowledge GraphsLink Prediction+5