000			a
999			_c30589 _d30589
008			220107b xxu||||| |||| 00| 0 eng d
020			_a9783030878856
082			_a518.1 _bERC
100			_aErciyes, K.
245			_aAlgebraic graph algorithms : a practical guide using Python
260			_bSpringer, _c2021 _aCham :
300			_axiii, 221 p. ; _bill., _c24 cm
365			_b37.99 _cEUR _d89.00
490			_aUndergraduate topics in computer science
504			_aIncludes bibliographical references and index.
520			_aThere has been unprecedented growth in the study of graphs, which are discrete structures that have many real-world applications. The design and analysis of algebraic algorithms to solve graph problems have many advantages, such as implementing results from matrix algebra and using the already available matrix code for sequential and parallel processing. Providing Python programming language code for nearly all algorithms, this accessible textbook focuses on practical algebraic graph algorithms using results from matrix algebra rather than algebraic study of graphs. Given the vast theory behind the algebraic nature of graphs, the book strives for an accessible, middle-ground approach by reviewing main algebraic results that are useful in designing practical graph algorithms on the one hand, yet mostly using graph matrices to solve the graph problems. Python is selected for its simplicity, efficiency and rich library routines; and with the code herein, brevity is forsaken for clarity. Topics and features: Represents graphs by algebraic structures, enabling new, robust methods for algorithm analysis and design Provides matroid-based solutions to some graph problems, including greedy algorithm problems Offers Python code that can be tested and modified for various inputs Supplies practical hints, where possible, for parallel processing associated with algebraic algorithms Links to a web page with supportive materials This clearly arranged textbook will be highly suitable for upper-level undergraduate students of computer science, electrical and electronic engineering, bioinformatics, and any researcher or person with background in discrete mathematics, basic graph theory and algorithms. Dr. Kayhan Erciyes is a full Professor in the Department of Software Engineering at Maltepe University, Istanbul, Turkey. His other publications include the Springer titles Discrete Mathematics and Graph Theory, Distributed Real-Time Systems, Guide to Graph Algorithms, Distributed and Sequential Algorithms for Bioinformatics, and Distributed Graph Algorithms for Computer Networks.
650			_aAlgorithm Analysis
650			_aProblem Complexity
650			_aDiscrete Mathematics in Computer Science
650			_aMathematical Applications in Computer Science
650			_aBellman-Ford algorithm
650			_aBellman-Ford algorithm
650			_a Centrality
650			_a Dijkstra's algorithm
650			_aEigenvalue
650			_aFloyd-Warshall algorithm
650			_aIsomorphism
650			_aGraph clustering;
650			_a Luby's algorithm
650			_aK-Core
650			_aRabin-Vazirani algorithm
650			_a Preis' algorithm
650			_a Span algorithm
650			_a Minimum spanning
650			_a Vertex betweenness centrality
650			_aWeighted matroid
650			_aMatrix
942			_2ddc _cBK