Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
This paper presents a hybrid approach to question answering in the clinical domain that combines techniques from summarization and information retrieval. We tackle a frequently-oc...
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Abstract— In this paper we present a novel intrusion detection architecture based on Idiotypic Network Theory (INIDIS), that aims at dealing with large scale network attacks feat...
Marek Ostaszewski, Pascal Bouvry, Franciszek Sered...
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...