Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Algebraic graph algorithmsa practica...
~
Erciyes, K.
Algebraic graph algorithmsa practical guide using Python /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Algebraic graph algorithmsby K. Erciyes.
Reminder of title:
a practical guide using Python /
Author:
Erciyes, K.
Published:
Cham :Springer International Publishing :2021.
Description:
xiii, 221 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Graph algorithms.
Online resource:
https://doi.org/10.1007/978-3-030-87886-3
ISBN:
9783030878863$q(electronic bk.)
Algebraic graph algorithmsa practical guide using Python /
Erciyes, K.
Algebraic graph algorithms
a practical guide using Python /[electronic resource] :by K. Erciyes. - Cham :Springer International Publishing :2021. - xiii, 221 p. :ill., digital ;24 cm. - Undergraduate topics in computer science,2197-1781. - Undergraduate topics in computer science..
1. Introduction -- 2. Graphs, Matrices and Matroids -- 3. Parallel Matrix Algorithm Kernel -- 4. Basic Graph Algorithms -- 5. Connectivity, Matching and Matroids -- 6. Subgraph Search -- 7. Analysis of Large Graphs -- 8. Clustering in Complex Networks -- 9. Kronecker Graphs -- 10. Sample Algorithms for Complex Networks.
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.
ISBN: 9783030878863$q(electronic bk.)
Standard No.: 10.1007/978-3-030-87886-3doiSubjects--Topical Terms:
455716
Graph algorithms.
LC Class. No.: QA166.245 / .E73 2021
Dewey Class. No.: 518.1
Algebraic graph algorithmsa practical guide using Python /
LDR
:03464nmm 22003375a 4500
001
613845
003
DE-He213
005
20211117134618.0
006
m d
007
cr nn 008maaau
008
220627s2021 sz s 0 eng d
020
$a
9783030878863$q(electronic bk.)
020
$a
9783030878856$q(paper)
024
7
$a
10.1007/978-3-030-87886-3
$2
doi
035
$a
978-3-030-87886-3
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA166.245
$b
.E73 2021
072
7
$a
UMB
$2
bicssc
072
7
$a
COM051300
$2
bisacsh
072
7
$a
UMB
$2
thema
082
0 4
$a
518.1
$2
23
090
$a
QA166.245
$b
.E65 2021
100
1
$a
Erciyes, K.
$3
731210
245
1 0
$a
Algebraic graph algorithms
$h
[electronic resource] :
$b
a practical guide using Python /
$c
by K. Erciyes.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
xiii, 221 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Undergraduate topics in computer science,
$x
2197-1781
505
0
$a
1. Introduction -- 2. Graphs, Matrices and Matroids -- 3. Parallel Matrix Algorithm Kernel -- 4. Basic Graph Algorithms -- 5. Connectivity, Matching and Matroids -- 6. Subgraph Search -- 7. Analysis of Large Graphs -- 8. Clustering in Complex Networks -- 9. Kronecker Graphs -- 10. Sample Algorithms for Complex Networks.
520
$a
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
0
$a
Graph algorithms.
$3
455716
650
0
$a
Python (Computer program language)
$3
215247
650
1 4
$a
Algorithm Analysis and Problem Complexity.
$3
273702
650
2 4
$a
Discrete Mathematics in Computer Science.
$3
274791
650
2 4
$a
Mathematical Applications in Computer Science.
$3
530811
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
830
0
$a
Undergraduate topics in computer science.
$3
559648
856
4 0
$u
https://doi.org/10.1007/978-3-030-87886-3
950
$a
Computer Science (SpringerNature-11645)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000207375
電子館藏
1圖書
電子書
EB QA166.245 .E65 2021 2021
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
https://doi.org/10.1007/978-3-030-87886-3
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login