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Outlier detection = techniques and a...

Ranga Suri, N. N. R.

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Outlier detection = techniques and applications : a data mining perspective /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Outlier detection/ by N. N. R. Ranga Suri, Narasimha Murty M, G. Athithan.
Reminder of title:	techniques and applications : a data mining perspective /
Author:	Ranga Suri, N. N. R.
other author:	Murty, M Narasimha.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xxii, 214 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Outlier Detection -- Research Issues in Outlier Detection -- Computational Preliminaries -- Outlier Detection in Categorical Data -- Outliers in High Dimensional Data.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	https://doi.org/10.1007/978-3-030-05127-3
ISBN:	9783030051273

Outlier detection = techniques and applications : a data mining perspective /
Ranga Suri, N. N. R.

Outlier detectiontechniques and applications : a data mining perspective /[electronic resource] :by N. N. R. Ranga Suri, Narasimha Murty M, G. Athithan. - Cham :Springer International Publishing :2019. - xxii, 214 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1551868-4394 ;. - Intelligent systems reference library ;v.155..

Introduction -- Outlier Detection -- Research Issues in Outlier Detection -- Computational Preliminaries -- Outlier Detection in Categorical Data -- Outliers in High Dimensional Data.

This book, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its significance in many contemporary applications. More specifically, the detection of fraud in e-commerce transactions and discovering anomalies in network data have become prominent tasks, given recent developments in the field of information and communication technologies and security. Accordingly, the book sheds light on specific state-of-the-art algorithmic approaches such as the community-based analysis of networks and characterization of temporal outliers present in dynamic networks. It offers a valuable resource for young researchers working in data mining, helping them understand the technical depth of the outlier detection problem and devise innovative solutions to address related challenges.

ISBN: 9783030051273

Standard No.: 10.1007/978-3-030-05127-3doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343 / R364 2019

Dewey Class. No.: 006.312

Outlier detection = techniques and applications : a data mining perspective /
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245 1 0 $a Outlier detection $h [electronic resource] : $b techniques and applications : a data mining perspective / $c by N. N. R. Ranga Suri, Narasimha Murty M, G. Athithan.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xxii, 214 p. : $b ill., digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4394 ; $v v.155
505 0 $a Introduction -- Outlier Detection -- Research Issues in Outlier Detection -- Computational Preliminaries -- Outlier Detection in Categorical Data -- Outliers in High Dimensional Data.
520 $a This book, drawing on recent literature, highlights several methodologies for the detection of outliers and explains how to apply them to solve several interesting real-life problems. The detection of objects that deviate from the norm in a data set is an essential task in data mining due to its significance in many contemporary applications. More specifically, the detection of fraud in e-commerce transactions and discovering anomalies in network data have become prominent tasks, given recent developments in the field of information and communication technologies and security. Accordingly, the book sheds light on specific state-of-the-art algorithmic approaches such as the community-based analysis of networks and characterization of temporal outliers present in dynamic networks. It offers a valuable resource for young researchers working in data mining, helping them understand the technical depth of the outlier detection problem and devise innovative solutions to address related challenges.
650 0 $a Data mining. $3 562972
650 0 $a Outliers (Statistics) $3 646508
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Data-driven Science, Modeling and Theory Building. $3 2210495
700 1 $a Murty, M Narasimha. $3 3383271
700 1 $a Athithan, G. $3 3383272
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830 0 $a Intelligent systems reference library ; $v v.155. $3 3383273
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950 $a Intelligent Technologies and Robotics (Springer-42732)