Knowledge Elicitation through Web-Based Data Mining Services
Knowledge is a vital component for organisational growth and data mining provides the technological basis for automated knowledge elicitation from data sources. The emergence of Application Service Providers hosting Internet-based data mining services is being seen as a viable alternative for organisations that value their knowledge resources but are constrained by the high cost of data mining software. In this paper, we present two alternative models of organisation for data mining service providers. We use the interaction protocols between organisations requiring data mining services and the service providers to motivate the need for specification of data mining task requests that adequately represent the requirements and constraints of the clients and also illustrate the importance of description mechanisms for data mining systems and services in order to support Internet delivery of such services. We present an XML-based approach for describing both, data mining task requests and the functionality and services of data mining service providers.
KeywordsService Provider Mobile Agent Document Type Definition Data Mining Task Data Mining Process
Unable to display preview. Download preview PDF.
- 1.Clark-Dickson, P., (1999), “Flag-fall for Application Rental”, Systems, (August), pp.23–31.Google Scholar
- 2.digiMine-URL: http://www.digiMine.com
- 3.e-Business XML (eb-XML). URL: http://www.ebxml.org
- 4.e-Speak. URL: http://www.e-speak.hp.com
- 5.Goldfarb, C,F., and Prescod, P., (1998), “The XML Handbook”, Prentice-Hall PTR, New Jersey, USA.Google Scholar
- 7.Han, J., Fu, Y., Wang, W., Koperski, K., and Zaiane, O., (1996), “DMQL: A Data Mining Query Language for Relational Databases”, Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD’96), Montreal, Canada, June.Google Scholar
- 9.Krishnaswamy, S., Zaslavsky, A., and Loke, S,W., (2000), “An Architecture to Support Distributed Data Mining Services in E-Commerce Environments”, Proceedings of the Second International Workshop on Advanced Issues in E-Commerce and Web-Based Information Systems, San Jose, Californinia, June 8-9, pp.238–246.Google Scholar
- 10.Krishnaswamy, S., Zaslavsky, A., and Loke, S,W., (2001), “Federated Data Mining Services and a Supporting XML Markup Language”, Proceedings of the 34th Annual Hawaii International Conference on System Sciences (HICSS-34), Hawaii, USA, January, In the “e-Services: Models and Methods for Design, Implementation and Delivery” mini-track of the “Decision Technologies for Management” track.Google Scholar
- 11.Krishnaswamy, S., Zaslavsky, A., and Loke, S,W., (2001), “Towards Data Mining Services on the Internet with a Multiple Service Provider Model-An XML Approach”, Submitted to the Journal of Electronic Commerce Research-Special Issue on E-Services and Operations.Google Scholar
- 12.Microsoft OLE DB for Data Mining, URL: http://www.microsoft.com/data/oledb/dm.html, March, 2000.
- 13.Ramu, A,T., (1998), “Incorporating Transportable Software Agents into a Wide Area High Performance Distributed Data Mining Systems”, Masters Thesis, University of Illinois, Chicago, USA.Google Scholar
- 14.Sarawagi, S., and Nagaralu, S,H., (2000), “Data Mining Models as Services on the Internet”, SIGKDD Explorations, Vol. 2, Issue. 1, http://www.acm.org/sigkdd/explorations/, accessed 01 April, 2001.
- 15.Universal Description, Discovery and Integration (UDDI). URL:http://www.uddi.org
- 16.Web Services Description Language. http://msdn.microsoft.com/xml/general/wsdl.asp