Recent combinations of semantic technology and artificial intelligence (AI) present new techniques to build intelligent systems that identify more precise results. Semantic AI in Knowledge Graphs locates itself at the forefront of this novel development, uncovering the role of machine learning to extend the knowledge graphs by graph mapping or corpus-based ontology learning.
Securing efficient results via the combination of symbolic AI and statistical AI such as entity extraction based on machine learning, text mining methods, semantic knowledge graphs, and related reasoning power, this book is the first of its kind to explore semantic AI and knowledge graphs. A range of topics are covered, from neuro-symbolic AI, explainable AI and deep learning to knowledge discovery and mining, and knowledge representation and reasoning.
A trailblazing exploration of semantic AI in knowledge graphs, this book is a significant contribution to both researchers in the field of AI and data mining as well as beginner academicians.
Author(s): Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz, and John Shawe-Taylor
Publisher: CRC Press
Year: 2023
Language: English
Pages: 217
Cover
Half Title
Title Page
Copyright Page
Contents
List of Figures
List of Tables
Preface
Editors
Contributors
1. Leveraging Semantic Knowledge Graphs in Educational Recommenders to Address the Cold-Start Problem
2. Modeling Event-Centric Knowledge Graph for Crime Analysis on Online News
3. Semantic Natural Language Processing for Knowledge Graphs Creation
4. MSE**: Multi-Modal Semantic Embeddings for Datasets with Several Positive Matchings
5. Text-Based Emergency Alert Framework for Under-Resourced Languages in Southern Nigeria
6. Knowledge Graphs in Healthcare
7. Explainable Machine Learning-Based Knowledge Graph for Modeling Location-Based Recreational Services from Users Profile
8. Building Knowledge Graph from Relational Database
Index
