Industrial databases often contain a large amount of unfilled information. During the knowledge discovery process one processing step is often necessary in order to remove these ...
Most of the complexity of common data mining tasks is due to the unknown amount of information contained in the data being mined. The more patterns and correlations are contained ...
Paolo Palmerini, Salvatore Orlando, Raffaele Pereg...
In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a prima...
The discovery of emerging patterns (EPs) is a descriptive data mining task defined for pre-classified data. It aims at detecting patterns which contrast two classes and has been ...
Annalisa Appice, Michelangelo Ceci, Carlo Malgieri...
Motivated by the need for unification of the field of data mining and the growing demand for formalized representation of outcomes of research, we address the task of constructi...
Mashup is a web technology that combines information from more than one source into a single web application. This technique provides a new platform for different data providers t...
Thomas Trojer, Benjamin C. M. Fung, Patrick C. K. ...
We present an unusual algorithm involving classification trees-CARTwheels--where two trees are grown in opposite directions so that they are joined at their leaves. This approach ...
Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. All...
Hans-Peter Kriegel, Matthias Schubert, Arthur Zime...