Towards MKDA: A Knowledge Discovery Assistant For Researches in Medicine
- Autori: Cannella, V.; Russo, G.; Peri, D.; Pirrone, R.; Ardizzone, E.
- Anno di pubblicazione: 2007
- Tipologia: Articolo in rivista (Articolo in rivista)
Nowadays doctors are generating a huge amount of raw data. These data, analyzed with data mining techniques, could be sources of new knowledge. Unluckily such tasks need skilled data analysts, and not so much researchers in Medicine are also data mining experts. In this paper we present a web based system for knowledge discovery assistance in Medicine able to advice a medical researcher in this kind of tasks. The user must define only the experiment specifications in a formal language we have defined. The system GUI helps users in their composition. Then the system plans a Knowledge Discovery Process (KDP) on the basis of rules in a knowledge base. Finally the system executes the KDP and produces a model as result. The system works through the co-operation of different web services specialized in different tasks. The system is still under development.