Abstract. This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, g...
An original method is proposed for spatial cluster detection of case event data. A selection order and the distance from the nearest neighbour are attributed to each point, once p...
Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant Colony Optimization (ACO) is one such algorithm based on s...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Abstract. We applied different clustering algorithms to the task of clustering multi-word terms in order to reflect a humanly built ontology. Clustering was done without the usual ...