Large-scale parallel data mining
Enregistré dans:
| Hovedforfatter: | |
|---|---|
| Andre forfattere: | |
| Format: | Livre numérique |
| Sprog: | Anglais |
| Udgivet: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Serier: | Lecture notes in computer science. Lecture notes in artificial intelligence
1759 |
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| Online adgang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Kommentar: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Large scale parallel data mining, Mohammed J. Zaki, Ching-Tien Ho (eds.), 2000, New York, Springer, 1 vol. (VIII-260 p.), Lecture notes in artificial intelligence, 3-540-67194-3 • Large-Scale Parallel Data Mining, Texte imprimé, 9783662175316 |
Indholdsfortegnelse:
- Large-Scale Parallel Data Mining
- Parallel and Distributed Data Mining: An Introduction
- Mining Frameworks
- The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project
- A High Performance Implementation of the Data Space Transfer Protocol (DSTP)
- Active Mining in a Distributed Setting
- Associations and Sequences
- Efficient Parallel Algorithms for Mining Associations
- Parallel Branch-and-Bound Graph Search for Correlated Association Rules
- Parallel Generalized Association Rule Mining on Large Scale PC Cluster
- Parallel Sequence Mining on Shared-Memory Machines
- Classification
- Parallel Predictor Generation
- Efficient Parallel Classification Using Dimensional Aggregates
- Learning Rules from Distributed Data
- Clustering
- Collective, Hierarchical Clustering from Distributed, Heterogeneous Data
- A Data-Clustering Algorithm on Distributed Memory Multiprocessors.