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Название: Data Science with Semantic Technologies: Theory, Practice and Application
Автор: Archana Patel, Narayan C. Debnath
Издательство: Wiley, Scrivener Publishing
Год: 2022
Страниц: 456
Язык: английский
Формат: pdf (true)
Размер: 41.0 MB
This book will serve as an important guide toward applications of Data Science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field. To create intelligence in data science, it becomes necessary to utilize semantic technologies which allow machine-readable representation of data. This intelligence uniquely identifies and connects data with common business terms, and it also enables users to communicate with data. Instead of structuring the data, semantic technologies help users to understand the meaning of the data by using the concepts of semantics, ontology, OWL, linked data, and knowledge-graphs. These technologies help organizations to understand all the stored data, adding the value in it, and enabling insights that were not available before. As data is the most important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization.
Автор: Archana Patel, Narayan C. Debnath
Издательство: Wiley, Scrivener Publishing
Год: 2022
Страниц: 456
Язык: английский
Формат: pdf (true)
Размер: 41.0 MB
This book will serve as an important guide toward applications of Data Science with semantic technologies for the upcoming generation and thus becomes a unique resource for scholars, researchers, professionals, and practitioners in this field. To create intelligence in data science, it becomes necessary to utilize semantic technologies which allow machine-readable representation of data. This intelligence uniquely identifies and connects data with common business terms, and it also enables users to communicate with data. Instead of structuring the data, semantic technologies help users to understand the meaning of the data by using the concepts of semantics, ontology, OWL, linked data, and knowledge-graphs. These technologies help organizations to understand all the stored data, adding the value in it, and enabling insights that were not available before. As data is the most important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization.