The growing production of maps is generating huge volume of data stored in large spatial databases. This huge volume of data exceeds the human analysis capabilities. Spatial data m...
The novel Time Series Data Mining (TSDM) framework is applied to analyzing financial time series. The TSDM framework adapts and innovates data mining concepts to analyzing time ser...
In this paper I define spatio-temporal regions as pairs consisting of a spatial and a temporal component and I define topological relations between them. Using the notion of rough ...
In meeting the challenges that resulted from the explosion of collected, stored, and transferred data, Knowledge Discovery in Databases or Data Mining has emerged as a new research...
Abstract. A new constrained model is discussed as a way of incorporating efficiently a priori expert knowledge into a clustering problem of a given individual set. The first innova...
: Relational representation of objects using graphs reveals much information that cannot be obtained by attribute value representations alone. There are already many databases that...
Data mining is a useful decision support technique, which can be used to find trends and regularities in warehouses of corporate data. A serious problem of its practical applicatio...
Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzew...
Although there is a growing need for multi-relational data mining solutions in KDD, the use of obvious candidates from the field of Inductive Logic Programming (ILP) has been limit...
Arno J. Knobbe, Arno Siebes, Hendrik Blockeel, Dan...