التفاصيل البيبلوغرافية
| العنوان: |
Machine Learning Meets the Semantic Web |
| المؤلفون: |
Kotis, Konstantinos Ilias, Zachila, Konstantina, Paparidis, Evaggelos |
| المصدر: |
Artificial Intelligence Advances; Vol. 3 , Iss. 1 (April 2021); 63-70 ; 2661-3220 |
| بيانات النشر: |
BILINGUAL PUBLISHING Group |
| سنة النشر: |
2021 |
| المجموعة: |
Bilingual Publishing Co. (BPC): E-Journals |
| مصطلحات موضوعية: |
Knowledge graph, Semantic web, Ontology, Machine learning, Deep learning, Graph neural networks |
| الوصف: |
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. |
| نوع الوثيقة: |
article in journal/newspaper |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
https://journals.bilpubgroup.com/index.php/aia/article/view/3178/2890Test; https://journals.bilpubgroup.com/index.php/aia/article/view/3178Test |
| الإتاحة: |
https://journals.bilpubgroup.com/index.php/aia/article/view/3178Test |
| حقوق: |
Copyright © 2021 Konstantinos Ilias Kotis, Konstantina Zachila, Evaggelos Paparidis |
| رقم الانضمام: |
edsbas.D3CA9F53 |
| قاعدة البيانات: |
BASE |
