Authors:
- Focuses on the fundamental principles of algorithm design for big data processing
- Covers advanced models of computation relevant for developing memory-efficient algorithms
- Advanced-level students and researchers focusing on computer and data science will find this book valuable as a text or reference book
Part of the book series: Advanced Information and Knowledge Processing (AI&KP)
Part of the book sub series: SpringerBriefs in Advanced Information and Knowledge Processing (BRIEFSAIKP)
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Table of contents (4 chapters)
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Front Matter
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Back Matter
About this book
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.
Authors and Affiliations
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Western Norway Research Institute, Sogndal, Norway
Rajendra Akerkar
Bibliographic Information
Book Title: Models of Computation for Big Data
Authors: Rajendra Akerkar
Series Title: Advanced Information and Knowledge Processing
DOI: https://doi.org/10.1007/978-3-319-91851-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-319-91850-1Published: 17 December 2018
eBook ISBN: 978-3-319-91851-8Published: 04 December 2018
Series ISSN: 1610-3947
Series E-ISSN: 2197-8441
Edition Number: 1
Number of Pages: VIII, 104
Number of Illustrations: 3 b/w illustrations
Topics: Algorithm Analysis and Problem Complexity, Data Mining and Knowledge Discovery, Linear Algebra, Models and Principles