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Centrality and diversity in search =...

Murty, M.N.

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Centrality and diversity in search = roles in A.I., machine learning, social networks, and pattern recognition /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Centrality and diversity in search/ by M.N. Murty, Anirban Biswas.
Reminder of title:	roles in A.I., machine learning, social networks, and pattern recognition /
Author:	Murty, M.N.
other author:	Biswas, Anirban.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xi, 94 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Searching -- Representation -- Clustering and Classification -- Ranking -- Centrality and Diversity in Social and Information Networks -- Conclusion.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-24713-3
ISBN:	9783030247133

Centrality and diversity in search = roles in A.I., machine learning, social networks, and pattern recognition /
Murty, M.N.

Centrality and diversity in searchroles in A.I., machine learning, social networks, and pattern recognition /[electronic resource] :by M.N. Murty, Anirban Biswas. - Cham :Springer International Publishing :2019. - xi, 94 p. :ill., digital ;24 cm. - SpringerBriefs in intelligent systems,2196-5498. - SpringerBriefs in intelligent systems..

Introduction -- Searching -- Representation -- Clustering and Classification -- Ranking -- Centrality and Diversity in Social and Information Networks -- Conclusion.

The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification. The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition.

ISBN: 9783030247133

Standard No.: 10.1007/978-3-030-24713-3doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q335 / .M87 2019

Dewey Class. No.: 006.3

Centrality and diversity in search = roles in A.I., machine learning, social networks, and pattern recognition /
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245 1 0 $a Centrality and diversity in search $h [electronic resource] : $b roles in A.I., machine learning, social networks, and pattern recognition / $c by M.N. Murty, Anirban Biswas.
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300 $a xi, 94 p. : $b ill., digital ; $c 24 cm.
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505 0 $a Introduction -- Searching -- Representation -- Clustering and Classification -- Ranking -- Centrality and Diversity in Social and Information Networks -- Conclusion.
520 $a The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification. The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition.
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