In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
: The fusion of data from different sensorial sources is the most promising method to increase robustness and reliability of environmental perception today. The paper presents an a...
Ulrich Scheunert, Philipp Lindner, Eric Richter, G...
In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system, named ARES that takes advantage of the ...
This paper describes a theoretical approach on data mining, information classifying and a global overview of our OntoExtractor application, concerning the analysis of incoming data...
Zhan Cui, Ernesto Damiani, Marcello Leida, Marco V...
We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...