| Title:
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DATA MINING IN TIME SERIES DATABASES
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| By: |
Abraham Kandel (Editor), Mark Last (Editor), Horst Bunke (Editor) |
| Format: |
Hardback |
| List price:
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£107.00 |
| Our price: |
£96.30 |
| Discount: |
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| You save:
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£10.70 |
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| ISBN 10: |
9812382909 |
| ISBN 13: |
9789812382900 |
| Availability: |
Reprinting. This item may be subject to delays or cancellation.
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rates
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| Stock: |
Currently 0 available |
| Publisher: |
WORLD SCIENTIFIC PUBLISHING CO PTE LTD |
| Pub. date: |
29 June, 2004 |
| Series: |
Series In Machine Perception And Artificial Intelligence 57 |
| Pages: |
204 |
| Description: |
An examination of state-of-the-art methodology for mining time series databases. The data mining methods presented 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. |
| Synopsis: |
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 book covers the 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 book 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. |
| Publication: |
Singapore |
| Imprint: |
World Scientific Publishing Co Pte Ltd |
| Returns: |
Returnable |