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Algorithms and models for network da...

Fouss, Francois.

Algorithms and models for network data and link analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Algorithms and models for network data and link analysisFrancois Fouss, Marco Saerens, Masashi Shimbo.
作者:	Fouss, Francois.
其他作者:	Saerens, Marco.
出版者:	New York :Cambridge University Press,2016.
面頁冊數:	xxv, 521 p. :ill., digital ;24 cm.
標題:	Network analysis (Planning)Mathematics.
電子資源:	https://doi.org/10.1017/CBO9781316418321
ISBN:	9781316418321$q(electronic bk.)

Algorithms and models for network data and link analysis
Fouss, Francois.

Algorithms and models for network data and link analysis[electronic resource] /Francois Fouss, Marco Saerens, Masashi Shimbo. - New York :Cambridge University Press,2016. - xxv, 521 p. :ill., digital ;24 cm.

Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. Matlab/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.

ISBN: 9781316418321$q(electronic bk.)Subjects--Topical Terms:

265412
Network analysis (Planning)
--Mathematics.

LC Class. No.: T57.85 / .F68 2016

Dewey Class. No.: 004.65

Algorithms and models for network data and link analysis
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520 $a Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. Matlab/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.
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