Add to ORKGIn tbis paper an attempt of employing network lpsources to solve a complex and time-consuming data mining problem is presented. The CLARANS is selected as the study objective. An improved CLARANS algorithm is first developed, in which the more inherent concurrency is explored. "hen its parallel implementation by using PVM mechanism and the running performance analysis are provided. The analysis results show the expected speed-up is obtained and demonstrate that some parallel data mining algorithm is more effective in a distributed network. Keywords: machine (PVM); distributed network. 1
(eng) We describe the compilation and execution of data-parallel languages for networks of workstati...
Abstract—Many networks display community structure which identifies groups of nodes within which con...
Wide area computer networks have become a basic part of today's computing infrastructure. These...
Recently major processor manufacturers have announced a dramatic shift in their paradigm to increas...
Parallel computing is a technique to solve a problem using many CPUs. To perform the parallel compu...
Abstract Recent years have shown the need of an automated process to discover interesting and hidden...
Introduction In general, a parallel computer is a computer that has multiple processors connected b...
Data mining is a set of methods used to mine hidden information from data. It mainly includes freque...
Parallel computing plays a crucial role in processing large-scale graph data. Complex network analys...
As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly ava...
Sequential pattern mining is an active field in the domain of knowledge discovery and has been widel...
As Machine Learning (ML) applications are becoming ever more pervasive, fully-trained systems are ma...
A parallel algorithm for solving distributed constraint networks (DCNs) is presented. The DCNs are c...
With the fast, continuous increase in the number and size of databases, parallel data mining is a na...
Abstract—Many networks display community structure which identifies groups of nodes within which con...
(eng) We describe the compilation and execution of data-parallel languages for networks of workstati...
Abstract—Many networks display community structure which identifies groups of nodes within which con...
Wide area computer networks have become a basic part of today's computing infrastructure. These...
Recently major processor manufacturers have announced a dramatic shift in their paradigm to increas...
Parallel computing is a technique to solve a problem using many CPUs. To perform the parallel compu...
Abstract Recent years have shown the need of an automated process to discover interesting and hidden...
Introduction In general, a parallel computer is a computer that has multiple processors connected b...
Data mining is a set of methods used to mine hidden information from data. It mainly includes freque...
Parallel computing plays a crucial role in processing large-scale graph data. Complex network analys...
As ML applications are becoming ever more pervasive, fully-trained systems are made increasingly ava...
Sequential pattern mining is an active field in the domain of knowledge discovery and has been widel...
As Machine Learning (ML) applications are becoming ever more pervasive, fully-trained systems are ma...
A parallel algorithm for solving distributed constraint networks (DCNs) is presented. The DCNs are c...
With the fast, continuous increase in the number and size of databases, parallel data mining is a na...
Abstract—Many networks display community structure which identifies groups of nodes within which con...
(eng) We describe the compilation and execution of data-parallel languages for networks of workstati...
Abstract—Many networks display community structure which identifies groups of nodes within which con...
Wide area computer networks have become a basic part of today's computing infrastructure. These...