Outlier Detection: Techniques and Applications: A Data Mining Perspective by G.

Description: Outlier Detection: Techniques and Applications by G. Athithan, N.N.R. Ranga Suri, Narasimha Murty M. 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. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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. Back Cover 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. Table of Contents Introduction.- Outlier Detection.- Research Issues in Outlier Detection.- Computational Preliminaries.- Outlier Detection in Categorical Data.- Outliers in High Dimensional Data. Feature Provides a comprehensive survey of the outlier detection problem including a list of issues, challenges and relevant literature Presents the latest methods for outlier detection with a special focus on categorical data Employs outlier detection principles in contemporary applications such as anomaly detection in network data and characterizing temporal anomalies/outliers in dynamic social networks Details ISBN3030051250 Author Narasimha Murty M. Series Intelligent Systems Reference Library Year 2019 ISBN-10 3030051250 ISBN-13 9783030051259 Format Hardcover Pages 214 Publication Date 2019-01-24 Language English DOI 10.1007/978-3-030-05127-3 Series Number 155 Edition 1st Imprint Springer Nature Switzerland AG Place of Publication Cham Country of Publication Switzerland Illustrations 3 Illustrations, color; 45 Illustrations, black and white; XXII, 214 p. 48 illus., 3 illus. in color. Subtitle A Data Mining Perspective Publisher Springer Nature Switzerland AG Edition Description 1st ed. 2019 DEWEY 006.3 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:126582451;

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