This paper proposes a novel ART-based neural architecture known as ART-C (ART under Constraints) that performs online clustering of pattern sequences subject to the constraints on the recognition category representation. Experiments on two real-life data sets show that ART-C produces reasonably good clustering qualities, with the added advantage of high efficiency. Keywords—Adaptive Resonance T...

Due to the growing popularity of social networking platforms, the analysis of online communities became in recent years a popular topic in different research fields. However, an aspect that has received only little attention is how the temporal aspects of social networks can be studied. This thesis bridges the gap and deals with the analysis of community structures in large social networks and ...

Motivation: Equipped with sophisticated biochemical measurement techniques we generate a massive amount of biomedical data that needs to be analyzed computationally. One long-standing challenge in automatic knowledge extraction is clustering. We seek to partition a set of objects into groups such that the objects within the clusters share common traits. Usually, we have given a similarity matri...

In the context of culture-aware robotics, we propose a method for the explicit, on-line mapping between cultural variables and robot behaviour parameters which relies on the linguistic variable formalism, fuzzy clustering and the principles of fuzzy controllers. As a case study, we consider the adaptation of the Human-Robot conversational distance to Hofstede’s cultural dimension of Individualism.

Résumé. Les modèles et outils OLAP actuels gèrent les dimensions d’analyse d’un entrepôt de données de manière statique. Par conséquent, les axes d’analyse restent souvent figés malgré l’évolution des besoins et des données. Dans cet article, nous proposons une approche d’évolution de schéma basée sur une technique de classification automatique. Pour cela, nous cherchons le meilleur regroupemen...

In this study, the controlability of the Kappa number in two cooking applications is investigated. The Kappa number is one of the quality measures in the pulp cooking process and usually the only on-line measurement. It is a measure of the residual lignin content in the pulp. The cooking of the pulp mainly takes place in the digester, where the significant part of the lignin is removed from the...

We present a new online algorithm for detecting overlapping communities. The main ingredients are a modification of an online k-means algorithm and a new approach to modelling overlap in communities. An evaluation on large benchmark graphs shows that the quality of discovered communities compares favourably to several methods in the recent literature, while the running time is significantly imp...

This report aims to give a brief overview of the current state of document clustering research and present recent developments in a well-organized manner. Clustering algorithms are considered with two hypothetical scenarios in mind: online query clustering with tight efficiency constraints, and offline clustering with an emphasis on accuracy. A comparative analysis of the algorithms is performe...

The management and processing of so-called data streams has recently become a topic of active research in several fields of computer science, notably database systems and data mining. A data stream can roughly be thought of as a transient, continuously increasing sequence of time-stamped data. In this paper, we consider the problem of clustering parallel streams of real-valued data, that is to ...