Data Science with Semantic Technologies: New Trends and Future Developments

✍ Scribed by Archana Patel, Narayan C. Debnath

Publisher: CRC Press
Year: 2023
Tongue: English
Leaves: 315
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies.

Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as can semantic technologies be able to facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists get benefited from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science?

This volume can serve as an important guide towards 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.

✦ Table of Contents

Cover
Half Title
Title
Copyright
Contents
Preface
List of Contributors
Chapter 1 What is Data Science
Chapter 2 Big Data and its Future
Chapter 3 Smart Warehouse Testbed: From Conceptual Framework to a Real Project
Chapter 4 Empirical Study on Sentiment Analysis
Chapter 5 Forecasting on Covid-19 Data Using ARIMAX Model
Chapter 6 ML-Based Method for Detecting and Alerting to Cyber Attacks
Chapter 7 Machine Learning in Natural Language Processing—Emerging Trends and Challenges
Chapter 8 Machine Learning and Future Directions
Chapter 9 Towards a Web Standard for Neuro-Symbolic Integration and Knowledge Representation Using Model Cards
Chapter 10 Semantic Web Technologies
Chapter 11 Data Science with Semantic Technologies
Chapter 12 Ontological Perspective in Cancer Care System
Chapter 13 Interoperability Frameworks: Data Fabric and Data Mesh Architectures
Chapter 14 Recommender System for E-Commerce: How Ontologies Support Recommendations
Index

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