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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...
| 主要な著者: | , , , |
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| フォーマット: | eBook |
| 言語: | English |
| 出版事項: |
San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) :
Morgan & Claypool,
2014.
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| シリーズ: | Synthesis digital library of engineering and computer science.
Synthesis lectures on data mining and knowledge discovery ; # 8. |
| 主題: | |
| オンライン･アクセス: | Abstract with links to full text |
| 要約: | 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. |
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| 記述事項: | Part of: Synthesis digital library of engineering and computer science. Series from website. |
| 物理的記述: | 1 PDF (xviii, 110 pages) : illustrations. Also available in print. |
| フォーマット: | Mode of access: World Wide Web. System requirements: Adobe Acrobat Reader. |
| 書誌: | Includes bibliographical references (pages 91-108). |
| ISBN: | 9781627053761 |
| ISSN: | 2151-0075 ; |
| アクセス: | Abstract freely available; full-text restricted to subscribers or individual document purchasers. |