Algebraic graph algorithms : a practical guide using Python (Record no. 30589)

000 -LEADER
fixed length control field a
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220107b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030878856
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 518.1
Item number ERC
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Erciyes, K.
245 ## - TITLE STATEMENT
Title Algebraic graph algorithms : a practical guide using Python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Springer,
Date of publication, distribution, etc 2021
Place of publication, distribution, etc Cham :
300 ## - PHYSICAL DESCRIPTION
Extent xiii, 221 p. ;
Other physical details ill.,
Dimensions 24 cm
365 ## - TRADE PRICE
Price amount 37.99
Price type code EUR
Unit of pricing 89.00
490 ## - SERIES STATEMENT
Series statement Undergraduate topics in computer science
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc There 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithm Analysis
Topical term or geographic name as entry element Problem Complexity
Topical term or geographic name as entry element Discrete Mathematics in Computer Science
Topical term or geographic name as entry element Mathematical Applications in Computer Science
Topical term or geographic name as entry element Bellman-Ford algorithm
Topical term or geographic name as entry element Bellman-Ford algorithm
Topical term or geographic name as entry element Centrality
Topical term or geographic name as entry element Dijkstra's algorithm
Topical term or geographic name as entry element Eigenvalue
Topical term or geographic name as entry element Floyd-Warshall algorithm
Topical term or geographic name as entry element Isomorphism
Topical term or geographic name as entry element Graph clustering;
Topical term or geographic name as entry element Luby's algorithm
Topical term or geographic name as entry element K-Core
Topical term or geographic name as entry element Rabin-Vazirani algorithm
Topical term or geographic name as entry element Preis' algorithm
Topical term or geographic name as entry element Span algorithm
Topical term or geographic name as entry element Minimum spanning
Topical term or geographic name as entry element Vertex betweenness centrality
Topical term or geographic name as entry element Weighted matroid
Topical term or geographic name as entry element Matrix
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent location Current location Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Checked out Date last seen Date last borrowed Koha item type
          DAIICT DAIICT 2022-01-05 3381.11 3 518.1 ERC 032780 2024-12-16 2024-05-13 2024-05-13 Books

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