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Abstract: Contents 1 Introduction 2 Overview of 7 different approaches for speeding up data mining in large databases 3 An overview of parallel processing for data mining 4 Parallel rule induction 5 Parallel Instance-Based Learning 6 Parallel Genetic Algorithms 7 Parallel Neural Networks 8 Conclusions Introduction. Problem: How to perform efficient data mining in very large databases. Natural solution: parallelism Performance issues: any sequential data mining algorithm: O(N) parallelism reduces this ... (Update)
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BibTeX entry: (Update)
@misc{ freitas-pkdd,
author = "Alex A. Freitas",
title = "PKDD'98 Tutorial on Scalable, High-Performance Data Mining with Parallel
Processing",
url = "citeseer.ist.psu.edu/freitas98pkdd.html" }
Citations (may not include all citations):298 Parallel database systems: the future of high performance da.. - DeWitt, Gray - 1992
145 SPRINT: a scalable parallel classifier for data mining - Shafer, Agrawal et al. - 1996
48 Parallel mining of association rules: design (context) - Agrawal, Shafer - 1996
42 Mining Very Large Databases with Parallel Processing (context) - Freitas, Lavington - 1998
28 Search-intensive concept induction - Giordana, Neri - 1995
28 Data surveyor: searching the nuggets in parallel (context) - Holsheimer, Kersten et al. - 1996
27 Scaling up: distributed machine learning with cooperation - Provost, Hennessy - 1996
23 Scaling up inductive learning with massive parallelism - Provost, Aronis - 1996
18 Distributed machine learning: scaling up with coarse-grained.. (context) - Provost, Hennessy - 1994
17 Parallel algorithms for discovery of association rules - Zaki, Parthasarathy et al. - 1997
13 A survey of methods for scaling up inductive learning algori.. - Provost, Kolluri - 1998
11 Set-Oriented Primitives to Support Data-Parallel Knowledge D.. (context) - Freitas - 1997
10 Scaling up inductive algorithms: an overview - Provost, Kolluri - 1997
10 A genetic programming framework for two data mining tasks: c.. - Freitas - 1997
8 Accelerated learning on the connection machine - Cook, Holder - 1990
8 Using SQL primitives and parallel DB servers to speed up kno.. - Freitas, Lavington - 1996
8 GA-MINER: parallel data mining with hierarchical genetic alg.. - Flockhart, Radcliffe - 1995
7 A network genetic algorithm for concept learning - Anglano, Giordana et al. - 1997
6 Data mining on parallel database systems (context) - Souza, Mattoso et al. - 1998
5 Decision trees on parallel processors - Kufrin - 1997
4 parallel classifier for data mining (context) - Srivastava, Singh et al. - 1997
4 A genetic algorithm-based approach to data mining (context) - Flockhart, Radcliffe - 1996
4 A coarse-grained parallel induction heuristic (context) - Pearson - 1994
3 An empirical performance study of the Ingres Search Accelera.. (context) - Anand, Bell et al. - 1994
3 Knowledge discovery from client-server databases - Dewhurst, Lavington - 1998
3 production rules in parallel (context) - Kufrin - 1997
2 DAFS: supporting the knowledge discovery process - McLaren, Babb et al. - 1997
2 Parallel data mining for very large relational databases (context) - Freitas, Lavington - 1996
1 Practical Applications of Knowledge Discovery and Data Minin.. (context) - Pass, the et al. - 1997
1 Application of WhiteCross MPP servers to data mining (context) - Mackin - 1997
1 Practical Applications of Knowledge Discovery & Data Mining (context) - Freitas, of et al. - 1998
Documents on the same site (http://www.ppgia.pucpr.br/~alex/tutorials.html):
GECCO-2001 Tutorial on Data Mining with Evolutionary Algorithms - Freitas (2001) (Correct)
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