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Outlier detection for temporal data /

Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Gupta, Manish (VerfasserIn), Aggarwal, Charu C. (VerfasserIn), Gao, Jing (VerfasserIn), Han, Jiawei (VerfasserIn)
Format: E-Book
Sprache:English
Veröffentlicht: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.
Schriftenreihe:Synthesis digital library of engineering and computer science.
Synthesis lectures on data mining and knowledge discovery ; # 8.
Schlagworte:
Online Zugang:Abstract with links to full text
Beschreibung
Zusammenfassung:Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book.
Beschreibung:Part of: Synthesis digital library of engineering and computer science.
Series from website.
Beschreibung:1 PDF (xviii, 110 pages) : illustrations.
Also available in print.
Format:Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Bibliographie:Includes bibliographical references (pages 91-108).
ISBN:9781627053761
ISSN:2151-0075 ;
Zugangseinschränkungen:Abstract freely available; full-text restricted to subscribers or individual document purchasers.