Representation Learning of Knowledge Graphs via Fine-Grained Relation Description Combinations

Knowledge representation learning attempts to represent entities and relations of knowledge graph in a continuous low-dimensional semantic space. However, most of the existing methods such as TransE, TransH, and TransR usually only utilize triples of knowledge graph. Other important information such...

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Bibliographic Details
Main Authors: Ming He, Xiangkun Du, Bo Wang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8653283/

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