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|b D38 2023
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|a UAMI
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|a Data science with semantic technologies.
|p Deployment and exploration /
|c edited by Archana Patel and Narayan C. Debnath.
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|a Deployment and exploration
|
250 |
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|a First edition.
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264 |
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1 |
|a Boca Raton, FL :
|b CRC Press,
|c 2023.
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|c Ã2023
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300 |
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|a 1 online resource (x, 236 pages)
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|a Includes bibliographical references and index.
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505 |
0 |
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|a 1. Machine Learning Meets the Semantic Web. 2. Knowledge Graphs: Connecting Information over the Semantic Web. 3. Latest Trends In Language Processing To Make Semantic Search More Semantic. 4. Semantic Information Retrieval Models. 5. Enterprise Application Development Using Semantic Web Languages for Semantic Data Modeling. 6. The Metadata Management for Semantic Ontology in Big Data. 7. Role of Knowledge Data Science during Covid-19. 8. Semantic Technologies in Next Era of Industry Revolution: Industry 4.0. 9. Semantic Interoperability Framework and its Application in Agriculture. 10. Design and Implementation of a Short Circuit Detection System Using Data Stream and Semantic Web Techniques. 11. Semantic-Based Access Control for Data Resources. 12. Ontological Engineering: Research Directions andReal-Life Applications. 13. Expert Systems in AI - Components, Applications, and Characteristics Focusing on Chatbot.
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520 |
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|a Gone are the days when data was interlinked with related data by humans and human interpretation was required. Data is no longer just data. It is now considered a Thing or Entity or Concept with meaning, so that a machine not only understands the concept but also extrapolates the way humans do. Data Science with Semantic Technologies: Deployment and Exploration, the second volume of a two-volume handbook set, provides a roadmap for the deployment of semantic technologies in the field of data science and enables the user to create intelligence through these technologies by exploring the opportunities and eradicating the challenges in the current and future time frame. In addition, this book offers the answer to various questions like: What makes a technology semantic as opposed to other approaches to data science? What is knowledge data science? How does knowledge data science relate to other fields? This book explores the optimal use of these technologies to provide the highest benefit to the user under one comprehensive source and title. As there is no dedicated book available in the market on this topic at this time, this book becomes a unique resource for scholars, researchers, data scientists, professionals, and practitioners. This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation.
|
588 |
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|a Description based on online resource; title from digital title page (viewed on August 09, 2023).
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
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|a Artificial intelligence.
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|a Information science.
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|a Semantic computing.
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|
700 |
1 |
|
|a Patel, Archana
|c (Lecturer in software engineering),
|e editor.
|
700 |
1 |
|
|a Debnath, N. C.
|q (Narayan C.),
|e editor.
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