| Description |
1 online resource (205 pages) |
| Contents |
Preface; Contents; Chapter 1 Segmenting Time Series: A Survey and Novel Approach E. Keogh, S. Chu, D. Hart and M. Pazzani; Chapter 2 A Survey of Recent Methods for Efficient Retrieval of Similar Time Sequences M.L. Hetland; Chapter 3 Indexing of Compressed Time Series E. Fink and K.B. Pratt; Chapter 4 Indexing Time-Series under Conditions of Noise M. Vlachos, D. Gunopulos and G. Das; Chapter 5 Change Detection in Classification Models Induced from Time Series Data G. Zeira, O. Maimon, M. Last and L. Rokach |
| Summary |
Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings |
| Notes |
Print version record |
| Subject |
Data mining.
|
|
Distributed databases.
|
|
Data mining
|
|
Distributed databases
|
| Form |
Electronic book
|
| Author |
Kandel, Abraham
|
|
Bunke, Horst
|
| ISBN |
9781423723028 |
|
1423723023 |
|
9789812565402 |
|
981256540X |
|
