Title :
A KDD Platform Based on the Application Service Provider Paradigm
Author :
Fumarola, Fabio ; Salvemini, Eliana ; Malerba, Donato
Author_Institution :
Dipt. di Inf., Univ. degli Studi di Bari, Bari
Abstract :
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.
Keywords :
Web services; data mining; data visualisation; decision making; groupware; small-to-medium enterprises; workflow management software; KD-ASP distributed collaborative data mining platform; KDD platform; Web service; application service provider paradigm; data pre-processing; data selection; data transformation; data visualization; digital district; global market; information technology; knowledge discovery process; public administration; small-and-medium enterprise; strategic decision making; workflow engine; Application specific processors; Collaboration; Collaborative work; Costs; Data mining; Data visualization; Engines; Globalization; Information technology; Web services; Distributed and parallel data mining/knowledge discovery; Frameworks for Business Intelligence (BI).; Knowledge discovery framework and process; collaborative data mining;
Conference_Titel :
Data Mining Workshops, 2008. ICDMW '08. IEEE International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-0-7695-3503-6
Electronic_ISBN :
978-0-7695-3503-6
DOI :
10.1109/ICDMW.2008.100