Overview
- Presents cutting-edge multimedia data mining research, including mobile multimedia
- Provides novel insights into the progression of the field, following the theme of disruptive innovation
- Bridges complex research and practice by exploring open source software, libraries and algorithms
- Includes supplementary material: sn.pub/extras
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About this book
This book provides fresh insights into the cutting edge of multimedia data mining, reflecting how the research focus has shifted towards networked social communities, mobile devices and sensors. The work describes how the history of multimedia data processing can be viewed as a sequence of disruptive innovations. Across the chapters, the discussion covers the practical frameworks, libraries, and open source software that enable the development of ground-breaking research into practical applications. Features: reviews how innovations in mobile, social, cognitive, cloud and organic based computing impacts upon the development of multimedia data mining; provides practical details on implementing the technology for solving real-world problems; includes chapters devoted to privacy issues in multimedia social environments and large-scale biometric data processing; covers content and concept based multimedia search and advanced algorithms for multimedia data representation, processing and visualization.
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Keywords
Table of contents (19 chapters)
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Front Matter
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Introduction
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Front Matter
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Mobile and Social Multimedia Data Exploration
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Front Matter
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Biometric Multimedia Data Processing
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Front Matter
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Multimedia Data Modeling, Search and Evaluation
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Front Matter
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Reviews
“Multimedia data mining and analytics: disruptive innovation highlights new applications in multimedia data mining, presenting fascinating techniques together with comprehensive cases in practice. … this book is valuable for the insight it provides related to the challenges faced by fast developing technologies, their current needs and future promise. It is a practical guide, a useful handbook for academies and industry practitioners who have interest in multimedia data analysis.” (Shanshan Qi, Information Technology & Tourism, Vol. 16, 2016)
Editors and Affiliations
About the editors
Aaron K. Baughman is a member of the Special Events Group at IBM (USA) for World Wide Sports. Previously, he was Technical Lead on a DeepQA Embed Research project that included an instance of the Jeopardy! Challenge.
Jiang (John) Gao is a Principal Scientist in the Advanced Development and Technology Group at Nokia USA, working on multimedia and mobile applications, data mining and computer vision.
Jia-Yu Pan is a software engineer at Google (USA), working on data mining and anomaly detection in big data.
Valery A. Petrushin is a Principal Scientist in the Research and Development Group at Opera Solutions (USA). His previous publications include the successful Springer title Multimedia Data Mining and Knowledge Discovery.
Bibliographic Information
Book Title: Multimedia Data Mining and Analytics
Book Subtitle: Disruptive Innovation
Editors: Aaron K. Baughman, Jiang Gao, Jia-Yu Pan, Valery A. Petrushin
DOI: https://doi.org/10.1007/978-3-319-14998-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-14997-4Published: 10 April 2015
Softcover ISBN: 978-3-319-34721-9Published: 05 October 2016
eBook ISBN: 978-3-319-14998-1Published: 31 March 2015
Edition Number: 1
Number of Pages: XIV, 454
Number of Illustrations: 35 b/w illustrations, 153 illustrations in colour
Topics: Multimedia Information Systems, Data Mining and Knowledge Discovery, Image Processing and Computer Vision, Signal, Image and Speech Processing, Innovation/Technology Management, Artificial Intelligence