The newly emerging field of Network Science deals with the tasks of modelling, comparing and summarizing large data sets that describe complex interactions. Because pairwise affin...
Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...
Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the...
Abstract. A framework for Multi Agent Data Mining (MADM) is described. The framework comprises a collection of agents cooperating to address given data mining tasks. The fundamenta...
Santhana Chaimontree, Katie Atkinson, Frans Coenen
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Abstract. One of the most important data mining tasks is discovery of frequently occurring patterns in sequences of events. Many algorithms for finding various patterns in sequenti...
Abstract— Sensor networks have evolved to a powerful infrastructure component for event monitoring in many application scenarios. In addition to simple filter and aggregation op...
Daniel Klan, Katja Hose, Marcel Karnstedt, Kai-Uwe...
Abstract. Most of the research in data mining has been focused on developing novel algorithms for specific data mining tasks. However, finding the theoretical foundations of data...
Using visualization techniques to assist conventional data mining tasks has attracted considerable interest in recent years. This paper addresses a challenging issue in the use of...