Add to ORKGThe HARVARD system is a general purpose system adequate for Knowledge Discover in Databases (KDD) running in general purpose PCs and based on distributed computing over a connected network of PCs. In this paper we discuss the extension of HARVARD to interact with a Grid Computing setting. This extension, called HARVARD-g, enable the HARVARD system to schedule task to the Grid and therefore largely increase its available computational power
The large amount of data collected today is quickly overwhelming researchers' abilities to inte...
Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collabor...
With pressure on Higher Educational Institutions to increase publication output, research using com...
Systems performing Data Mining analysis are usually dedicated and expensive. They often require spec...
A process of Knowledge Discovery in Databases (KDD) involving large amounts of data requires a consi...
When data mining and knowledge discovery techniques must be used to analyze large amounts of data, h...
In many industrial, scientific and commercial applications, it is often necessary to analyze large d...
High-performance computing increasingly occurs on computational grids composed of heterogeneous an...
High-performance computing increasingly occurs on “computational grids” composed of heterogeneous an...
Abstract—In this paper, we discuss a Grid data mining system based on the MapReduce paradigm of comp...
Managing and efficiently analysing the vast amounts of data produced by a huge variety of data sourc...
Grid computing is applying the resources of many computers in a network to a single problem at the s...
Abstract: Grid computing is nothing but the computing environment in which the resources are shared ...
Industrial processes require sufficient computational resources and their high availability, along w...
MapReduce is a powerful data processing platform for commercial and academic applications. In this p...
The large amount of data collected today is quickly overwhelming researchers' abilities to inte...
Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collabor...
With pressure on Higher Educational Institutions to increase publication output, research using com...
Systems performing Data Mining analysis are usually dedicated and expensive. They often require spec...
A process of Knowledge Discovery in Databases (KDD) involving large amounts of data requires a consi...
When data mining and knowledge discovery techniques must be used to analyze large amounts of data, h...
In many industrial, scientific and commercial applications, it is often necessary to analyze large d...
High-performance computing increasingly occurs on computational grids composed of heterogeneous an...
High-performance computing increasingly occurs on “computational grids” composed of heterogeneous an...
Abstract—In this paper, we discuss a Grid data mining system based on the MapReduce paradigm of comp...
Managing and efficiently analysing the vast amounts of data produced by a huge variety of data sourc...
Grid computing is applying the resources of many computers in a network to a single problem at the s...
Abstract: Grid computing is nothing but the computing environment in which the resources are shared ...
Industrial processes require sufficient computational resources and their high availability, along w...
MapReduce is a powerful data processing platform for commercial and academic applications. In this p...
The large amount of data collected today is quickly overwhelming researchers' abilities to inte...
Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collabor...
With pressure on Higher Educational Institutions to increase publication output, research using com...