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# Knowledge Graph Completion Edit

18 papers with code · Knowledge Base

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# Knowledge Graph Completion via Complex Tensor Factorization

22 Feb 2017Accenture/AmpliGraph

In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.

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# TuckER: Tensor Factorization for Knowledge Graph Completion

28 Jan 2019ibalazevic/TuckER

Knowledge graphs are structured representations of real world facts.

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# One-Shot Relational Learning for Knowledge Graphs

Knowledge graphs (KGs) are the key components of various natural language processing applications.

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# Learning Sequence Encoders for Temporal Knowledge Graph Completion

In line with previous work on static knowledge graphs, we propose to address this problem by learning latent entity and relation type representations.

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# Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences

17 Feb 2019TaoMiner/joint-kg-recommender

In this paper, we jointly learn the model of recommendation and knowledge graph completion.

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# A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization

In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object).

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# ProjE: Embedding Projection for Knowledge Graph Completion

16 Nov 2016Sujit-O/pykg2vec

In this work, we present a shared variable neural network model called ProjE that fills-in missing information in a knowledge graph by learning joint embeddings of the knowledge graph's entities and edges, and through subtle, but important, changes to the standard loss function.

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# Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of research on knowledge base completion (also known as relation prediction).

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# Open-World Knowledge Graph Completion

Knowledge Graphs (KGs) have been applied to many tasks including Web search, link prediction, recommendation, natural language processing, and entity linking.

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# DSKG: A Deep Sequential Model for Knowledge Graph Completion

30 Oct 2018nju-websoft/DSKG

Knowledge graph (KG) completion aims to fill the missing facts in a KG, where a fact is represented as a triple in the form of $(subject, relation, object)$.

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