Abstract. Frequent itemsets and association rules are generally accepted concepts in analyzing item-based databases. The Apriori-framework was developed for analyzing categorical d...
Predicting the interests of a user in information is an important process in personalized information systems. In this paper, we present a way to create prediction engines that al...
Mark van Setten, Mettina Veenstra, Anton Nijholt, ...
When using communication in multi-robot systems it's often not desirable to choose an form of communication that separates the messages from the physical environment in which...
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...