Data mining in time series databases /
Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This manual examines state-of-the-art methodology for mining time series databases. The novel data mining methods presented in t...
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| Other Authors: | , , |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
New Jersey ; London :
World Scientific,
©2004.
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| Series: | Series in machine perception and artificial intelligence ;
v. 57. |
| Subjects: | |
| Online Access: | CONNECT |
| Summary: | Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This manual examines state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the text also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed. |
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| Item Description: | EBSCO eBook Academic Comprehensive Collection North America |
| Physical Description: | 1 online resource (xi, 192 pages) : illustrations. |
| Bibliography: | Includes bibliographical references. |
| ISBN: | 1423723023 9781423723028 9789812382900 9812382909 1281347760 9781281347763 |
