Sanju Tiwari, Fernando Ortiz-Rodríguez, Sarra Ben Abbès, Patience Usoro Usip, Rim Hantach
Aim of the book
Semantic AI emerged with technical and organizational advantages and presented as another machine learning algorithm. It considered a variety of concepts that were extracted from AI such as speech recognition, natural language processing, information extraction, classification, recommendations, etc. The combination of Semantic Technology and Artificial Intelligence presents new techniques to build intelligent systems to find results more precisely. Current research shows that sometimes AI initiatives fail due to inappropriate data or poor quality of data. Semantic AI is the combination of symbolic AI and statistical AI such as entity extraction based on machine learning and text mining methods, based on semantic knowledge graphs and related reasoning power to obtain efficient results.
This book will explore the major roles of AI with semantic technologies to present a semantic enhanced AI architecture with semantic knowledge graphs. The primary aim of this book is to discover the role of machine learning to extend knowledge graphs by graph mapping or corpus-based ontology learning. According to the literature, there is no book published on Semantic AI and Knowledge Graph so the proposed theme is more suitable to make strong selling points.
Publication: The proposed book will be published with Taylor & Francis, CRC Press and Scopus Indexed.