Embedding Learning with Triple Trustiness on Noisy Knowledge Graph
Embedding learning on knowledge graphs (KGs) aims to encode all entities and relationships into a continuous vector space, which provides an effective and flexible method to implement downstream knowledge-driven artificial intelligence (AI) and natural language processing (NLP) tasks. Since KG const...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-11-01
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Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/21/11/1083 |