Enriching Translation-Based Knowledge Graph Embeddings Through Continual Learning
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Summary
The experimental results from two tasks of knowledge graph embedding prove that the proposed method not only incorporates new knowledge of new triples into the existing embedding successfully but also preserves the knowledge of the current embedding.
- Type
- article
- Published
- 2018-01-01
- Cited by
- 25
- References
- 43
- Access
- Open access
- OpenAlex
- https://openalex.org/W2897702399
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:53279151
Keywords
Embedding, Knowledge graph, Computer science, Forgetting, Graph
References
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- Freebase: a collaboratively created graph database for structuring human knowledge
- A latent factor model for highly multi-relational data
- Reasoning With Neural Tensor Networks for Knowledge Base Completion
- Translating Embeddings for Modeling Multi-relational Data
- Holographic Embeddings of Knowledge Graphs
- Information Extraction over Structured Data: Question Answering with Freebase
- Knowledge Graph and Text Jointly Embedding
- Learning Entity and Relation Embeddings for Knowledge Graph Completion
- Knowledge Graph Embedding via Dynamic Mapping Matrix
Cited by
- Leveraging Semantics for Incremental Learning in Multi-Relational Embeddings
- Disentangle-based Continual Graph Representation Learning
- Continual Learning of Knowledge Graph Embeddings
- A Survey on Knowledge Graph Embeddings for Link Prediction
- Towards the Modelling of Veillance based Citizen Profiling using Knowledge Graphs
- Building a Scalable and Interpretable Bayesian Deep Learning Framework for Quality Control of Free Form Surfaces
- TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
- Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs
- A Comprehensive “Real-World Constraints”-Aware Requirements Engineering Related Assessment and a Critical State-of-the-Art Review of the Monitoring of Humans in Bed
- Graph Lifelong Learning: A Survey
- History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion
- Enhancing missing facts inference in knowledge graph using triplet subgraph attention embeddings
- Continual Learning on Graphs: Challenges, Solutions, and Opportunities
- Towards Continual Knowledge Graph Embedding via Incremental Distillation
- Overview of knowledge reasoning for knowledge graph
- Fast and Continual Knowledge Graph Embedding via Incremental LoRA
- Neurosymbolic Methods for Dynamic Knowledge Graphs
- Knowledge Graph Completion for Activity Recommendation in Business Process Modeling
- DebiasedKGE: Towards Mitigating Spurious Forgetting in Continual Knowledge Graph Embedding
- Towards Improving Long-Tail Entity Predictions in Temporal Knowledge Graphs through Global Similarity and Weighted Sampling
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