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Big Data Analytics for Human-Computer Interactions: A New Era of Computation

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Title: Big Data Analytics for Human-Computer Interactions: A New Era of Computation
Description: Big Data is playing a vital role in HCI projects across a range of industries: healthcare, cybersecurity, forensics, education, business organizations, and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Working on HCI projects requires specific skill sets to implement IT solutions.Big Data Analytics for Human-Computer Interactions: A New Era of Computation is a comprehensive guide that discusses the evolution of Big Data in Human Computer Interaction from promise to reality. This book provides an introduction to Big Data and HCI, followed by an overview of the state-of-the-art algorithms for processing big data, Subsequent chapters also explain the characteristics, applications, opportunities and challenges of big data systems, by describing theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in designing HIC systems. The book also presents solutions for analyzing complex patterns in user data and improving productivity. Readers will be able to understand the technology that drives big data solutions in HCI projects and understand its capacity in transforming an organization.The book also helps the reader to understand HCI system design and explains how to evaluate an application portfolio that can be used when selecting pilot projects.This book is a resource for researchers, students, and professionals interested in the fields of HCI, artificial intelligence, data analytics, and computer engineering.
Authors: Kuldeep, Singh Kaswan, Anupam, Baliyan, Jagjit, Singh Dhatterwal, Om, Prakash Kaiwartya
Resource Type: eBook.
Subjects: Machine learning, Internet of things, Big data
Categories: COMPUTERS / Human-Computer Interaction (HCI), COMPUTERS / Artificial Intelligence / General
Database: eBook Collection (EBSCOhost)
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  Data: Big Data is playing a vital role in HCI projects across a range of industries: healthcare, cybersecurity, forensics, education, business organizations, and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Working on HCI projects requires specific skill sets to implement IT solutions.Big Data Analytics for Human-Computer Interactions: A New Era of Computation is a comprehensive guide that discusses the evolution of Big Data in Human Computer Interaction from promise to reality. This book provides an introduction to Big Data and HCI, followed by an overview of the state-of-the-art algorithms for processing big data, Subsequent chapters also explain the characteristics, applications, opportunities and challenges of big data systems, by describing theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in designing HIC systems. The book also presents solutions for analyzing complex patterns in user data and improving productivity. Readers will be able to understand the technology that drives big data solutions in HCI projects and understand its capacity in transforming an organization.The book also helps the reader to understand HCI system design and explains how to evaluate an application portfolio that can be used when selecting pilot projects.This book is a resource for researchers, students, and professionals interested in the fields of HCI, artificial intelligence, data analytics, and computer engineering.
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        Type: prePub
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      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Internet of things
        Type: general
      – SubjectFull: Big data
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      – TitleFull: Big Data Analytics for Human-Computer Interactions: A New Era of Computation
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 30
              M: 04
              Type: profile
              Y: 2024
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