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001 978-3-319-73235-0
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008 180413s2018 gw | s |||| 0|eng d
020 _a9783319732350
_9978-3-319-73235-0
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
_2thema
082 0 4 _a005.1
_223
100 1 _aErciyes, K.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aGuide to Graph Algorithms
_h[electronic resource] :
_bSequential, Parallel and Distributed /
_cby K Erciyes.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVIII, 471 p. 247 illus., 1 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTexts in Computer Science,
_x1868-0941
500 _aAcceso multiusuario
505 0 _aIntroduction -- Part I: Fundamentals -- Introduction to Graphs -- Graph Algorithms -- Parallel Graph Algorithms -- Distributed Graph Algorithms -- Part II: Basic Graph Algorithms -- Trees and Graph Traversals -- Weighted Graphs -- Connectivity -- Matching -- Independence, Domination and Vertex Cover -- Coloring -- Part III: Advanced Topics -- Algebraic and Dynamic Graph Algorithms -- Analysis of Large Graphs -- Complex Networks -- Epilogue -- Appendix A: Pseudocode Conventions -- Appendix B: Linear Algebra Review.
520 _aThis clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. 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 methods. Topics and features: Presents a comprehensive analysis of sequential graph algorithms Offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms Describes methods for the conversion between sequential, parallel and distributed graph algorithms Surveys methods for the analysis of large graphs and complex network applications Includes full implementation details for the problems presented throughout the text Provides additional supporting material at an accompanying website 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. Dr. K. Erciyes is an emeritus professor of computer engineering at Ege University, Turkey. His other publications include the Springer titles Distributed Graph Algorithms for Computer Networks and Distributed and Sequential Algorithms for Bioinformatics.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aAlgorithms.
650 0 _aComputer science-Mathematics.
650 1 4 _aAlgorithm Analysis and Problem Complexity.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I16021
650 2 4 _aDiscrete Mathematics in Computer Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I17028
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319732343
776 0 8 _iPrinted edition:
_z9783319732367
776 0 8 _iPrinted edition:
_z9783030103385
830 0 _aTexts in Computer Science,
_x1868-0941
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-73235-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cLIBRO_ELEC
999 _c243009
_d243008