Editors:
Contains proceedings from 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2019), Coimbatore, India, December 12-13, 2019
Features topics ranging from Data Science for Cognitive Analysis to Internet-Based Cognitive Platforms
Includes contributions from researchers, academics, and professionals from around the world
Part of the book series: EAI/Springer Innovations in Communication and Computing (EAISICC)
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Table of contents (35 papers)
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Front Matter
About this book
This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature details on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2019) took place in Coimbatore, India on December 12-13, 2019.
- Contains proceedings from 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2019), Coimbatore, India, December 12-13, 2019;
- Features topics ranging from Data Science for Cognitive Analysis to Internet-Based Cognitive Platforms;
- Includes contributions from researchers, academics, and professionals from around the world.
Keywords
- Computer Science
- Informatics
- Conference Proceedings
- Research
- Applications
- Big Data
- Data Science
- Machine Learning
Editors and Affiliations
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Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, India
Anandakumar Haldorai
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Department of Computer Science and Engineering, Presidency University, Bengaluru, India
Arulmurugan Ramu
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Electronics and Communication Engg, Sri Eshwar College of Engineering, Coimbatore, India
Sudha Mohanram
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Dept of Info Mgmt, Sec 3, Natl Taichung Univ of Sci & Tech, Taichung, Taiwan
Mu-Yen Chen
About the editors
Dr. Arulmurugan Ramu is a Professor, Presidency University, Bangalore, India. His research focuses on the automatic interpretation of images and related problems in machine learning and optimization. His main research interest is in vision, particularly high-level visual recognition. He has authored more than 35 papers in major computer vision and machine learning conferences and journals. He is the recipient of Ph.D. degrees in Information and Communication Engineering from the Anna University at Chennai, M.Tech in Information Technology Anna University of Technology and B.Tech degree in Information Technology. He is guided many Ph.D. research scholar under the area of Image Processing using Machine Learning. He is an Associate Editor of Inderscience IJISC journal. He is awarded as Best Young Faculty Award 2018 and nominated for Best Young Researcher Award (Male) by International Academic and Research Excellence Awards (IARE-2019).
Dr. Sudha Mohanram, has graduated from Government College of Engineering, Salem and has obtained her Masters in Engineering from Coimbatore Institute of Technology. She has completed her PhD in Electrical Engineering in Anna University Chennai in the year 2010. She started her teaching profession as a Lecturer in Government College of Technology, Coimbatore. She possesses 20 years of teaching experience. When she was about 13 years into teaching profession, her family founded Sri Eshwar College of Engineering in 2008. She has been playing the role of Secretary till 2011 and became the Principal of the institution in 2011. She has steered the institution to be one of the most sought after institutions in Coimbatore, within a short span of time through its laudable achievement in Academic excellence and Placement. She has published many papers in leading journals. She is a member of IEEE and EAI research group.
Dr. Mu-Yen Chen is a Professor of Information Management at National Taichung University of Science and Technology, Taiwan. He received his PhD from Information Management from National Chiao-Tung University in Taiwan. His current research interests include artificial intelligent, soft computing, bio-inspired computing, data mining, deep learning, context-awareness, machine learning, and financial engineering, with more than 100 publications in these areas. He has co-edited 12 special issues in International Journals (e.g. Computers in Human Behavior, Applied Soft Computing, Soft Computing, Information Fusion, Neurocomputing, Journal of Medical and Biological Engineering, The Electronic Library, Library High Tech). He has served as Editor in Chief and Associate Editor of international journals [e.g. International Journal of Big Data and Analytics in Healthcare, IEEE Access, Human-centric Computing and Information Sciences, Journal of Information Processing Systems, International Journal of Social and Humanistic Computing] while he is an editorial board member on several SCI journals.
Bibliographic Information
Book Title: 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing
Book Subtitle: BDCC 2019
Editors: Anandakumar Haldorai, Arulmurugan Ramu, Sudha Mohanram, Mu-Yen Chen
Series Title: EAI/Springer Innovations in Communication and Computing
DOI: https://doi.org/10.1007/978-3-030-47560-4
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-47559-8Published: 01 October 2020
Softcover ISBN: 978-3-030-47562-8Published: 02 October 2021
eBook ISBN: 978-3-030-47560-4Published: 30 September 2020
Series ISSN: 2522-8595
Series E-ISSN: 2522-8609
Edition Number: 1
Number of Pages: XI, 504
Number of Illustrations: 50 b/w illustrations, 221 illustrations in colour
Topics: Communications Engineering, Networks, Computational Intelligence, Data Mining and Knowledge Discovery, Computer Communication Networks