This article explores the utility of neural network ensembles in knowledge discovery and integration. A novel neural network ensemble model KBNNE (Knowledge-Based Neural Network E...
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Knowledge Discovery in Databases (KDD) has become a very attractive discipline both for research and industry within last few years. Its goal is to extract pieces of knowledge or `...
Subgroup discovery aims at finding interesting subsets of a classified example set that deviates from the overall distribution. The search is guided by a so-called utility function...
The aim of this work is to survey and reflect on the various ways to integrate visualization and data mining techniques toward a mixed-initiative knowledge discovery taking the be...