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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...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Gupta, Manish (مؤلف), Aggarwal, Charu C. (مؤلف), Gao, Jing (مؤلف), Han, Jiawei (مؤلف)
التنسيق: كتاب الكتروني
اللغة:English
منشور في: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.
سلاسل:Synthesis digital library of engineering and computer science.
Synthesis lectures on data mining and knowledge discovery ; # 8.
الموضوعات:
الوصول للمادة أونلاين:Abstract with links to full text
الوصف
الملخص: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.
وصف المادة:Part of: Synthesis digital library of engineering and computer science.
Series from website.
وصف مادي:1 PDF (xviii, 110 pages) : illustrations.
Also available in print.
التنسيق:Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
بيبلوغرافيا:Includes bibliographical references (pages 91-108).
ردمك:9781627053761
تدمد:2151-0075 ;
وصول:Abstract freely available; full-text restricted to subscribers or individual document purchasers.