The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory.
Models of Computation for Big Data,
covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.
Series
Edition
Language
Place of publication
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
3 s/w Abbildungen
VIII, 104 p. 3 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 7 mm
Weight
ISBN-13
978-3-319-91850-1 (9783319918501)
DOI
10.1007/978-3-319-91851-8
Schweitzer Classification
Rajendra Akerkar is a professor of information technology at Western Norway Research Institute, Norway. He has 23 years of research and teaching experience in artificial intelligent systems, semantic technologies and big data science. His recent research focuses on real world use of big data, and social media analysis in a wide set of semantic dimensions. He has held senior positions in the key academic conference committees, journal boards and review committees in those fields and he has supervised Ph.D. and research M.Sc. projects in intelligent systems, web intelligence and data science. He has managed 12 international ICT initiatives, and data-intensive research & development projects for more than 17 years.
Dr Priti Srinivas Sajja (b.1970) joined the faculty of the Department of Computer Science, Sardar Patel University, India in 1994 and is presently working as a Professor. She received her M.S. (1993) and Ph.D (2000) in Computer Science from the Sardar Patel University. Her research interests include knowledge-based systems, soft computing, multi-agent systems, and software engineering. She has 152 publications in books, book chapters, journals, and in the proceedings of national and international conferences out of which five publications have won best research paper awards. She is co-author of 'Knowledge-Based Systems' and 'Intelligent Technologies for Web Applications' published in the USA. She is supervising work of a few doctoral research scholars while six candidates have completed their Ph.D research under her guidance. She was Principal Investigator of a major research project funded by UGC, India. She is serving as a member on the editorial board of many international science journals and served as a program committee member for various international conferences.
