Cognitive Computing: Theory and Applications

Informationen zum Autor Vijay V. Raghavan, Alfred and Helen Lamson Endowed Professor in Computer Science, The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, USA. Prof Raghavan also serves as the Director of the NSF-sponsored Industry/ University Cooperative Research Center for Visual and Decision Informatics. In this role, he co-ordinates several multi-institutional, industry-driven research projects and manages a budget of over $500K/year. From 1997 to 2003, he led a $2.3M research and development project in close collaboration with the USGS National Wetlands Research Center and with the Department of Energy's Office of Science and Technical Information on creating a digital library with data mining capabilities incorporated. His research interests are in Big Data, data mining, information retrieval, machine learning and Internet computing. He has published over 250 peer-reviewed research papers --appearing in top-level journals and proceedings - that cumulatively accord him an h-index of 31, based on citations. He has served as major advisor for 24 doctoral students and has garnered $10 million in external funding. Besides substantial technical expertise, Dr. Raghavan has vast experience managing interdisciplinary and multi- institutional collaborative projects. He has also directed industry-sponsored research, for companies such as GE Healthcare and Araicom Life Sciences L.L.C., on projects pertaining to Neuro-imaging based dementia detection and literature-based biomedical hypotheses generation, respectively. Venkat N. Gudivada is a professor and chair of the Computer Science Department at East Carolina University. Prior to this, he was a professor and founding chair of the Weisberg Division of Computer Science at Marshall University. His industry tenure spans over six years as a vice president for Wall Street companies in the New York City area including Merrill Lynch (now Bank of America Merrill Lynch) and Financial Technologies International (now GoldenSource). Previous academic tenure includes work at the University of Michigan, University of Missouri, and Ohio University. He has published over 90 peer-reviewed technical articles and rendered professional service in various roles including conference program chair, keynote speaker, program committee member, and guest editor of IEEE journals. Gudivada's research sponsors include National Science Foundation (NSF), National Aeronautics and Space Administration (NASA), U.S. Department of Energy, U.S. Department of Navy, U.S. Army Research Office, MU Foundation, and WV Division of Science and Research. His current research interests encompass Big Data Management, High Performance Computing, Information Retrieval, Image and Natural Language Processing, and Personalized Learning. Gudivada received a PhD degree in Computer Science from the University of Louisiana at Lafayette. Venu Govindaraju, SUNY Distinguished Professor of Computer Science and Engineering, is the founding director of the Center for Unified Biometrics and Sensors. He received his Ph.D. from the University at Buffalo, State University of New York. His research focus is on machine learning and pattern recognition in the domains of Document Image Analysis and Biometrics. Prof. Govindaraju has co-authored over 400 refereed scientific papers. His seminal work in handwriting recognition was at the core of the first handwritten address interpretation system used by the US Postal Service. He has been a Principal or Co-Investigator of sponsored projects funded for about $65 million dollars. Prof. Govindaraju has supervised the dissertations of 30 doctoral students. He has served on the editorial boards of premier journals. Prof. Govindaraju is a Fellow of the ACM (Association of Computing Machinery), IEEE (Institute of Electrical and Electronics Engineers), AAAS (American Association for the Advancement of Science), the IAPR (Inte...

List of contents

A. Fundamentals and Principles1. Cognitive Computing: Concepts, Architectures, Systems and ApplicationsVenkat N Gudivada2. Cognitive Computing and Neural Networks: Reverse Engineering the BrainAnthony S. Maida
B. Complex Analytics and Machine Learning 3. Visual Analytic Decision Making Environments for Large-Scale Time Evolving Graphs Siva R. Venna, Raju N. Gottumukkala and Vijay V. Raghavan 4. CyGraph: Graph-Based Analytics and Visualization for Cybersecurity Steven Noel, Eric Harley, Kam Him Tam, Michael Limiero and Matthew Share 5. Cognitive Analytics: Going Beyond Big Data Analytics and Machine LearningVenkat N Gudivada, Mohammad T. Irfan, Ehsan Fathi and Dhana L Rao6. A Cognitive Random Forest: An Intra- and Inter-Cognitive Computing for Big Data Classification Under Cune-ConditionShan Suthaharan7. Bayesian Additive Regression Tree for Seemingly Unrelated Regression with Automatic Tree Selection Sounak Chakraborty
C. Applications8. Cognitive Systems for the Food-Water-Energy Nexus Vincent P. A. Lonij and Jean-Baptiste Fiot9. Cognitive Computing Applications in Education and LearningMohammad T. Irfan and Venkat N Gudivada10. Large Scale Data Enabled Evolution of Spoken Language Research and ApplicationsS. Jothilakshmi and Venkat N Gudivada11. The Internet of Things and Cognitive ComputingFlorence D. Hudson

Product details

• Authors: Venu Govindaraju, Govindaraju Venu, Venkat N. Gudivada, Vijay Gudivada Raghavan, Vijay V Raghavan, Vijay V. Raghavan, C. R. Rao, C.R. Rao, Vijay V Raghavan
• Publisher: ELSEVIER SCIENCE BV
• Languages: English
• Product format: Hardback
• Released: 30.09.2016
• EAN: 9780444637444
• ISBN: 978-0-444-63744-4
• No. of pages: 402
• Series: Handbook of Statistics; Handbook of Statistics
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > General, dictionaries; Artificial Intelligence, COMPUTERS / Artificial Intelligence / General