2008 IEEE International Conference on Data Mining Workshops (2008)
Dec. 15, 2008 to Dec. 19, 2008
Nowadays, Small and Medium Enterprises (SMEs) are forced to compete on a global market and to make strategic decisions in short periods of time. In order to allow SMEs access to information technologies which can support their competition on a global scale, public administrations are fostering the setting up of Digital Districts. In this paper, we describe a distributed collaborative data mining platform, named KD-ASP, developed for a Digital District. It is based on the application service provider (ASP) paradigm, which allows SMEs accessing to data mining services over a network and to cut down costs for their acquisition, upgrading and maintenance. KD-ASP allows the users to collaborate on the design of a knowledge discovery process whose execution is then demanded to a workflow engine. Tasks involved in a process are classified as data selection, pre-processing, data transformation, data mining and data visualization, and are made available as Web services.
Knowledge discovery framework and process, Distributed and parallel data mining/knowledge discovery, collaborative data mining, Frameworks for Business Intelligence (BI).
F. Fumarola, D. Malerba and E. Salvemini, "A KDD Platform Based on the Application Service Provider Paradigm," 2008 IEEE International Conference on Data Mining Workshops(ICDMW), vol. 00, no. , pp. 983-986, 2008.