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. Introduction.- Outlier Detection.- Research Issues in Outlier Detection.- Computational Preliminaries.- Outlier Detection in Categorical Data.- Outliers in High Dimensional Data.
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EAN: 9783030051259
UPC: 9783030051259
ISBN: 9783030051259
MPN: N/A
Item Length: 23.4 cm
Subject Area: Social Research
Item Height: 235 mm
Item Width: 155 mm
Series: Intelligent Systems Reference Library
Author: N. N. R. Ranga Suri, Narasimha Murty M, G. Athithan
Publication Name: Outlier Detection: Techniques and Applications: a Data Mining Perspective
Format: Hardcover
Language: English
Publisher: Springer Nature Switzerland A&G
Subject: Computer Science, Biology
Publication Year: 2019
Type: Textbook
Item Weight: 524 g
Number of Pages: 214 Pages