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Data science has been playing a vital role in almost all major
fields. Many researchers are interested in the development of IT
applications, which are user-driven with a focus on issues. This
can be addressed using data science. User-driven research and data
science have gained much attention from many private, public, and
government organizations and research institutions. The Handbook of
Research on Designing User Interfaces With a Data Science Approach
promotes the inclusion of more diversified users for user-centered
designs of applications across domains and analyzes user data with
a data science approach for effective and user-friendly user
interface designs. It introduces the foundations of advanced topics
of human-computer interaction, particularly with user-centered
designs and techniques. Covering topics such as artificial neural
networks, natural dialog systems, and machine learning, this book
is an essential resource for faculty, research scholars, industry
professionals, students of higher education, mathematicians, data
scientists, interaction designers, visual designers, software
engineers, user experience researchers, accessibility engineers,
cognitive system engineers, academicians, and libraries.
Data science has been playing a vital role in almost all major
fields. Many researchers are interested in the development of IT
applications, which are user-driven with a focus on issues. This
can be addressed using data science. User-driven research and data
science have gained much attention from many private, public, and
government organizations and research institutions. Designing User
Interfaces With a Data Science Approach promotes the inclusion of
more diversified users for user-centered designs of applications
across domains and analyzes user data with a data science approach
for effective and user-friendly user interface designs. It
introduces the foundations of advanced topics of human-computer
interaction, particularly with user-centered designs and
techniques. Covering topics such as artificial neural networks,
natural dialog systems, and machine learning, this book is an
essential resource for faculty, research scholars, industry
professionals, students of higher education, mathematicians, data
scientists, interaction designers, visual designers, software
engineers, user experience researchers, accessibility engineers,
cognitive system engineers, academicians, and libraries.
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