Knowledge Graph Representation Learning With Multi-Scale Capsule-Based Embedding Model Incorporating Entity Descriptions

A Knowledge Graph (KG) is a directed graph with nodes as entities and edges as relations. KG representation learning (KGRL) aims to embed entities and relations in a KG into continuous low-dimensional vector spaces, so as to simplify the manipulation while preserving the inherent structure of the KG...

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Bibliographic Details
Main Authors: Jingwei Cheng, Fu Zhang, Zhi Yang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9247098/