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Data Mining In Time Series Databases.
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 b...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore :
World Scientific,
2004.
|
| Edición: | 57th ed. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
| 007 | cr mn|---||||| | ||
| 008 | 091207s2004 si o 000 0 eng d | ||
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| 020 | |a 9781423723028 |q (electronic bk.) | ||
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| 035 | |a (OCoLC)475947809 | ||
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| 082 | 0 | 4 | |a 005.741 |
| 084 | |a 54.64 |2 bcl | ||
| 049 | |a UAMI | ||
| 100 | 1 | |a Last, Mark. | |
| 245 | 1 | 0 | |a Data Mining In Time Series Databases. |
| 250 | |a 57th ed. | ||
| 260 | |a Singapore : |b World Scientific, |c 2004. | ||
| 300 | |a 1 online resource (205 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 520 | |a 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. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Distributed databases. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Bases de données réparties. | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Distributed databases |2 fast | |
| 700 | 1 | |a Kandel, Abraham. | |
| 700 | 1 | |a Bunke, Horst. | |
| 776 | 1 | |z 9789812382900 | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=238334 |z Texto completo |
| 938 | |a EBL - Ebook Library |b EBLB |n EBL238334 | ||
| 994 | |a 92 |b IZTAP | ||