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Knowledge Graph Completion

26 papers with code ยท Knowledge Base
Subtask of Knowledge Graphs

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Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes

15 May 2020

Recently, link prediction algorithms based on neural embeddings have gained tremendous popularity in the Semantic Web community, and are extensively used for knowledge graph completion.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION

Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework

15 Apr 2020

A generative network (GN) takes two elements of a (subject, predicate, object) triple as input and generates the vector representation of the missing element.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION QUESTION ANSWERING RELATIONAL REASONING TRIPLE CLASSIFICATION

Exploring Effects of Random Walk Based Minibatch Selection Policy on Knowledge Graph Completion

12 Apr 2020

In this paper, we have explored the effects of different minibatch sampling techniques in Knowledge Graph Completion.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION

Reinforced Anytime Bottom Up Rule Learning for Knowledge Graph Completion

9 Apr 2020

In this paper, we are concerned with two extensions of AnyBURL.

KNOWLEDGE GRAPH COMPLETION

Improving the Utility of Knowledge Graph Embeddings with Calibration

2 Apr 2020

This paper addresses machine learning models that embed knowledge graph entities and relationships toward the goal of predicting unseen triples, which is an important task because most knowledge graphs are by nature incomplete.

CALIBRATION KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION

Is Aligning Embedding Spaces a Challenging Task? A Study on Heterogeneous Embedding Alignment Methods

21 Feb 2020

Representation Learning of words and Knowledge Graphs (KG) into low dimensional vector spaces along with its applications to many real-world scenarios have recently gained momentum.

ENTITY DISAMBIGUATION KNOWLEDGE GRAPH COMPLETION QUESTION ANSWERING REPRESENTATION LEARNING

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

8 Jan 2020

Large-scale knowledge graphs (KGs) are shown to become more important in current information systems.

KNOWLEDGE GRAPH COMPLETION RELATIONAL REASONING ZERO-SHOT LEARNING

NoiGAN: NOISE AWARE KNOWLEDGE GRAPH EMBEDDING WITH GAN

ICLR 2020

Knowledge graph has gained increasing attention to recent years for its successful applications of numerous tasks.

KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING

Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds

ICLR 2020

We study theoretical properties of embedding methods for knowledge graph completion under the missing completely at random assumption.

KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING

Knowledge Graph Embedding via Graph Attenuated Attention Networks

IEEE Access 2019

However, these methods assign the same weights on the relation path in the knowledge graph and ignore the rich information presented in neighbor nodes, which result in incomplete mining of triple features.

KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION RELATIONAL REASONING