Advances in data science : methodologies and applications / Gloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain, editors.
Phillips-Wren, Gloria E.; Esposito, Anna.; Jain, L. C.
2021
QA76 .A48 2021eb
Available Online

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Advances in data science : methodologies and applications / Gloria Phillips-Wren, Anna Esposito, Lakhmi C. Jain, editors.
ISBN
9783030518707 (electronic bk.)
3030518701 (electronic bk.)
9783030518714 (print)
303051871X
9783030518721 (print)
3030518728
3030518698
9783030518691
DOI
https://doi.org/10.1007/978-3-030-51870-7
Published
Cham : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xvii, 333 pages)
Item Number
10.1007/978-3-030-51870-7 doi
10.1007/978-3-030-51
Call Number
QA76 .A48 2021eb
Dewey Decimal Classification
004
Summary
Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Added Author
Phillips-Wren, Gloria E.
Esposito, Anna.
Jain, L. C.
Series
Intelligent systems reference library ; v. 189.
Available in Other Form
Print version: 9783030518691
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Introduction to Big Data and Data Science: Methods and Applications
Towards Abnormal Behavior Detection of Elderly People Using Big Data
A Survey on Automatic Multimodal Emotion Recognition in the Wild
"Speech Melody and Speech Content Didn't Fit Together"
Differences in Speech Behavior for Device Directed and Human Directed Interactions
Methods for Optimizing Fuzzy Inference Systems
The Dark Side of Rationality. Does Universal Moral Grammar Exist?
A New Unsupervised Neural Approach to Stationary and Non-stationary Data
Fall Risk Assessment Using New sEMG-Based Smart Socks
Describing Smart City Problems with Distributed Vulnerability
Feature Set Ensembles for Sentiment Analysis of Tweets
Supporting Data Science in Automotive and Robotics Applications with Advanced Visual Big Data Analytics
Classification of Pilot Attentional Behavior Using Ocular Measures
Audio Content-Based Framework for Emotional Music Recognition
Neuro-Kernel-Machine Network Utilizing Deep Learning and Its Application in Predictive Analytics in Smart City Energy Consumption
Learning Approaches for Facial Expression Recognition in Ageing Adults: A Comparative Study.

Browse Subjects

Show more subjects...

Statistics

from
to
Export