Parallel algorithms for hierarchical clustering
Parallel Computing
Data mining with neural networks: solving business problems from application development to decision support
Mining Very Large Databases with Parallel Processing
Mining Very Large Databases with Parallel Processing
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
Strategies for Parallel Data Mining
IEEE Concurrency
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Scalable Parallel Data Mining for Association Rules
IEEE Transactions on Knowledge and Data Engineering
KNOWLEDGE GRID: High Performance Knowledge Discovery on the Grid
GRID '01 Proceedings of the Second International Workshop on Grid Computing
A Parallel Genetic Algorithm for Concept Learning
Proceedings of the 6th International Conference on Genetic Algorithms
Scalable Parallel Clustering for Data Mining on Multicomputers
IPDPS '00 Proceedings of the 15 IPDPS 2000 Workshops on Parallel and Distributed Processing
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Large-Scale Parallel Data Clustering
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Generating C4.5 production rules in parallel
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A Uniform Parallel Optimization Method for Knowledge Discovery Grid
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
A uniform parallel optimization method for data mining grid
First International Workshop on Artificial Intelligence in Grid Computing
From Parallel Data Mining to Grid-Enabled Distributed Knowledge Discovery
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Performance characterization of data mining benchmarks
Proceedings of the 2010 Workshop on Interaction between Compilers and Computer Architecture
A parallel optimization framework in grid environment
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Future Generation Computer Systems
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Knowledge discovery in databases or data mining is the semi-automated analysis of large volumes of data, looking for the relationships and knowledge that are implicit in large volumes of data and are 'interesting' in the sense of impacting an organization's practice. Data mining and knowledge discovery on large amounts of data can benefit of the use of parallel computers both to improve performance and quality of data selection. This paper presents and discusses different forms of parallelism that can be exploited in data mining techniques and algorithms. For the main data mining techniques, such as rule induction, clustering algorithms, decision trees, genetic algorithms, and neural networks, the possible ways to exploit parallelism are presented and discussed in detail. Finally, some promising research directions in the parallel data mining research area are outlined.