Large-Scale Parallel Data Mining
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2000.
|
| Έκδοση: | 1st ed. 2000. |
| Σειρά: | Lecture Notes in Artificial Intelligence ;
1759 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.
