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Machine Learning Meets the Semantic Web

Authors
  • Konstantinos, Ilias Kotis
  • Konstantina, Zachila
  • Evaggelos, Paparidis
Journal
Artificial Intelligence Advances
Publisher
Bilingual Publishing Co
Publication Date
Apr 30, 2021
Volume
3
Issue
1
Identifiers
DOI: 10.30564/aia.v3i1.3178
Source
Bilingual Publishing
Keywords
License
Green

Abstract

Remarkable progress in research has shown the efficiency of Knowledge Graphs (KGs) in extracting valuable external knowledge in various domains. A Knowledge Graph (KG) can illustrate high-order relations that connect two objects with one or multiple related attributes.The emerging Graph Neural Networks (GNN) can extract both object characteristics and relations from KGs. This paper presents how Machine Learning (ML) meets the Semantic Web and how KGs are related to Neural Networks and Deep Learning. The paper also highlights important aspects of this area of research, discussing open issues such as the bias hidden in KGs at different levels of graph representation.

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