With the increasing need of data availability and cloud-based services, distributed database management has already gained a maximum momentum in technological advancement. With the data stored in distributed manner, performing distributed data mining is encountering challenges especially when the data is real-time, non-static, highly heterogeneous, unstructured, etc. Usually, such forms of distributed data management are only effective if it is managed over grid infrastructure, which offers a suitable arena to the technology to provide better performance. However, research work considering distributed data mining over grid interface has not been nurtured to the best point in the research community as compared to conventional data mining app...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceAlthough many Data Mining tasks have been parallelized and can thus be execute...
Abstract. Nowadays, the process of data mining is one of the most important topics in scientific and...
Data mining technology has emerged as a means for identifying patterns and trends from large quantit...
Data mining tasks considered a very complex business problem. In this research, we study the enhance...
This chapter gives an evaluation of the benefits of grid-based technology from a data miner's perspe...
Abstract — Distributed sources of voluminous data have raised the need of distributed data mining. C...
Abstract: Grid computing is nothing but the computing environment in which the resources are shared ...
The grid-based computing paradigm has attracted much attention in recent years. The sharing of distr...
The grid-based computing paradigm has attracted much attention in recent years. The sharing of distr...
In this paper, we discuss requirements for a distributed data mining platform, putting the requireme...
This paper reports a UK Economic and Social Research Council project that is exploring the use of Gr...
In many industrial, scientific and commercial applications, it is often necessary to analyze large d...
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Di...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceAlthough many Data Mining tasks have been parallelized and can thus be execute...
Abstract. Nowadays, the process of data mining is one of the most important topics in scientific and...
Data mining technology has emerged as a means for identifying patterns and trends from large quantit...
Data mining tasks considered a very complex business problem. In this research, we study the enhance...
This chapter gives an evaluation of the benefits of grid-based technology from a data miner's perspe...
Abstract — Distributed sources of voluminous data have raised the need of distributed data mining. C...
Abstract: Grid computing is nothing but the computing environment in which the resources are shared ...
The grid-based computing paradigm has attracted much attention in recent years. The sharing of distr...
The grid-based computing paradigm has attracted much attention in recent years. The sharing of distr...
In this paper, we discuss requirements for a distributed data mining platform, putting the requireme...
This paper reports a UK Economic and Social Research Council project that is exploring the use of Gr...
In many industrial, scientific and commercial applications, it is often necessary to analyze large d...
The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Di...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceVery large data volumes and high computation costs in data mining applications...
International audienceAlthough many Data Mining tasks have been parallelized and can thus be execute...