000			03053nam a22001937a 4500
005			20180410154208.0
008			180410b xxu||||| |||| 00| 0 eng d
020			_a9781138033894
028			_aBrijwasi Book Distributors _b;H-87,Lalita Park ,Laxmi Nagar,Delhi-110092 _c;BW/004773 _d;07/04/2018
082			_a003.72 ERC
100			_aKayhan Erciyes
245			_aComplex networks _b: an algorithmic perspective _c/Kayhan Erciyes
260			_aBoca Raton _b : CRC Press/Taylor & Francis _c, 2014
300			_axxi, 294 pages _c;24 cm
505			_aNetwork science is a rapidly emerging field of study that encompasses mathematics, computer science, physics, and engineering. A key issue in the study of complex networks is to understand the collective behavior of the various elements of these networks. Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, few books focus on the algorithmic aspects of complex network analysis. Filling this need, Complex Networks: An Algorithmic Perspective supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher and student of complex networks. This book is about specifying, classifying, designing, and implementing mostly sequential and also parallel and distributed algorithms that can be used to analyze the static properties of complex networks. Providing a focused scope which consists of graph theory and algorithms for complex networks, the book identifies and describes a repertoire of algorithms that may be useful for any complex network. Provides the basic background in terms of graph theory Supplies a survey of the key algorithms for the analysis of complex networks Presents case studies of complex networks that illustrate the implementation of algorithms in real-world networks, including protein interaction networks, social networks, and computer networks Requiring only a basic discrete mathematics and algorithms background, the book supplies guidance that is accessible to beginning researchers and students with little background in complex networks. To help beginners in the field, most of the algorithms are provided in ready-to-be-executed form. While not a primary textbook, the author has included pedagogical features such as learning objectives, end-of-chapter summaries, and review questions
520			_a"Network science is an emerging field of study that encompasses mathematics, computer science, physics, and engineering. An important issue in the study of complex networks is to understand the collective behavior of the elements of these networks. Although the results from graph theory have proven to be powerful in investigating the structures of complex networks, there are few books on the algorithmic aspects of complex network analysis. Filling this need, this book supplies the basic theoretical algorithmic and graph theoretic knowledge needed by every researcher of complex network
700			_aKayhan Erciyes
942			_cMDL
999			_c49316 _d49316