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.

  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

  Autorentext
  Dr. Anandakumar Haldorai, Professor (Associate) and Research Head in Department of Computer Science and Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, India. He has received his Master's in Software Engineering from PSG College of Technology, Coimbatore and PhD in Information and Communication Engineering from PSG College of Technology under, Anna University, Chennai. His research areas include Big Data, Cognitive Radio Networks, Mobile Communications and Networking Protocols. He has authored more than 82 research papers in reputed International Journals and IEEE conferences. He has authored 7 books and many book chapters with reputed publishers such as Springer and IGI. He is an Editor in Cheif of Keai- Elsevier IJIN and Editor in Chief of of Inderscience IJISC. also served as a reviewer for IEEE, IET, Springer, Inderscience and Elsevier journals. He is also the guest editor of many journals with Elsevier, Springer, Inderscience, etc. He has been the General Chair, Session Chair, and Panelist in several conferences. He is senior member of IEEE, IET, ACM and Fellow member of EAI research group.

  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 leadingjournals. 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.

  Inhalt

Introduction.- Data Science for Cognitive Analysis.- Real-Time Ubiquitous Data Science.- Platform for Privacy Preserving Data Science.- Internet-Based Cognitive Platform.- Social Data Relationship Ranking on Internet.- Data Applications of Cognitive Communication.- Statistics, data filtering to decide what data to keep and informative aspects.- Machine Learning and Big Data.- Big Algorithms and Software Development.- Smart Grid Cyber Security Data Analysis.- Smart City Initiative and Big Applications.- Natural Language Generation.- Sustainable Computer and Communication Model.- Knowledge Engineering, Representation and Extraction.- Decision Making under Uncertainty.- Cloud Big Computing Services.- Scalable Data Management Systems.- Future Advancements.- Conclusion.