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Review

2018

Review

2018

Abstract Graphs, such as social networks, word co-occurrence networks, and communication networks, occur naturally in various… Expand

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Review

2018

Review

2018

Graph is an important data representation which appears in a wide diversity of real-world scenarios. Effective graph analytics… Expand

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Review

2017

Review

2017

Knowledge graph (KG) embedding is to embed components of a KG including entities and relations into continuous vector spaces, so… Expand

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Highly Cited

2016

Highly Cited

2016

Graph embedding algorithms embed a graph into a vector space where the structure and the inherent properties of the graph are… Expand

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Highly Cited

2015

Highly Cited

2015

Knowledge graphs are useful resources for numerous AI applications, but they are far from completeness. Previous work such as… Expand

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Highly Cited

2015

Highly Cited

2015

Knowledge graph completion aims to perform link prediction between entities. In this paper, we consider the approach of knowledge… Expand

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Highly Cited

2015

Highly Cited

2015

This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful… Expand

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Highly Cited

2014

Highly Cited

2014

We deal with embedding a large scale knowledge graph composed of entities and relations into a continuous vector space. TransE is… Expand

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Highly Cited

2007

Highly Cited

2007

A large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to… Expand

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Highly Cited

2005

Highly Cited

2005

In the last decades, a large family of algorithms - supervised or unsupervised; stemming from statistic or geometry theory - have… Expand

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