Search results for "Software mining"
showing 3 items of 3 documents
Does relevance matter to data mining research?
2008
Data mining (DM) and knowledge discovery are intelligent tools that help to accumulate and process data and make use of it. We review several existing frameworks for DM research that originate from different paradigms. These DM frameworks mainly address various DM algorithms for the different steps of the DM process. Recent research has shown that many real-world problems require integration of several DM algorithms from different paradigms in order to produce a better solution elevating the importance of practice-oriented aspects also in DM research. In this chapter we strongly emphasize that DM research should also take into account the relevance of research, not only the rigor of it. Und…
Towards MKDA: A Knowledge Discovery Assistant for Researches in Medicine
2007
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 pr…
Knowledge management challenges in knowledge discovery systems
2006
Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting the most appropriate technique(s) for a problem at hand, since in the real domain area it is infeasible to perform a comparison of all applicable techniques. The main goal of this paper is to consider the limitations of data-driven approaches and propose a knowledge-driven approach to enhance the use of multiple data-mining strategies in a knowledge discovery system. We introduce the concept of (meta-) knowledge management, which is aimed to organize a systematic process of (meta-) knowledge capture and refinement o…