Guide to Graph Algorithms by K. Erciyes
Estimated delivery 3-12 business days
Format Hardcover
Condition Brand New
Description This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, approximation algorithms and heuristics for such problems and implementation of advanced graph structures in machine learning. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic and features:Presents a comprehensive analysis of sequential graph algorithmsOffers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithmsDescribes methods for the conversion between sequential, parallel and distributed graph algorithmsSurveys methods for the analysis of large graphs and complex network applicationsIncludes full implementation details for the problems presented throughout the textSurveys advanced graph structures used in artificial intelligence with code examplesReviews graph machine-intelligence methods This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms and machine . K. Erciyesis professor of computer engineering at Yaar University, Turkey. His other publications include the Springer titles Distributed Graph Algorithms for Computer Networks, Distributed and Sequential Algorithms for Bioinformatics,and Guide to Distributed Algorithms.
Details
- ISBN 3032052939
- ISBN-13 9783032052933
- Title Guide to Graph Algorithms
- Author K. Erciyes
- Format Hardcover
- Year 2026
- Pages 529
- Publisher Springer Nature Switzerland AG
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