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Knowledge Graph Completion

31 papers with code · Knowledge Base
Subtask of Knowledge Graphs

Knowledge graphs $G$ are represented as a collection of triples $\{(h, r, t)\}\subseteq E\times R\times E$, where $E$ and $R$ are the entity set and relation set. The task of Knowledge Graph Completion is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.

Source: One-Shot Relational Learning for Knowledge Graphs

Benchmarks

Greatest papers with code

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.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION RELATIONAL REASONING

A Survey on Knowledge Graphs: Representation, Acquisition and Applications

2 Feb 2020shaoxiongji/awesome-knowledge-graph

In this survey, we provide a comprehensive review on knowledge graph covering overall research topics about 1) knowledge graph representation learning, 2) knowledge acquisition and completion, 3) temporal knowledge graph, and 4) knowledge-aware applications, and summarize recent breakthroughs and perspective directions to facilitate future research.

GRAPH REPRESENTATION LEARNING KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING RELATIONAL REASONING

Knowledge Representation Learning: A Quantitative Review

28 Dec 2018shaoxiongji/awesome-knowledge-graph

Knowledge representation learning (KRL) aims to represent entities and relations in knowledge graph in low-dimensional semantic space, which have been widely used in massive knowledge-driven tasks.

INFORMATION RETRIEVAL KNOWLEDGE GRAPH COMPLETION LANGUAGE MODELLING QUESTION ANSWERING RECOMMENDATION SYSTEMS RELATION EXTRACTION REPRESENTATION LEARNING TRIPLE CLASSIFICATION

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.

FEATURE ENGINEERING KNOWLEDGE GRAPH COMPLETION

Mining Implicit Entity Preference from User-Item Interaction Data for Knowledge Graph Completion via Adversarial Learning

28 Mar 2020RUCDM/KB4Rec

Our generator is isolated from user interaction data, and serves to improve the performance of the discriminator.

KNOWLEDGE GRAPH COMPLETION

KG-BERT: BERT for Knowledge Graph Completion

7 Sep 2019yao8839836/kg-bert

Knowledge graphs are important resources for many artificial intelligence tasks but often suffer from incompleteness.

KNOWLEDGE GRAPH COMPLETION LANGUAGE MODELLING LINK PREDICTION TRIPLE CLASSIFICATION

One-Shot Relational Learning for Knowledge Graphs

EMNLP 2018 xwhan/One-shot-Relational-Learning

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

KNOWLEDGE GRAPH COMPLETION RELATIONAL REASONING

Learning Sequence Encoders for Temporal Knowledge Graph Completion

EMNLP 2018 nle-ml/mmkb

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

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION