In this work a method for detecting distance-based outliers in data streams is presented. We deal with the sliding window model, where outlier queries are performed in order to de...
We describe a data mining framework that derives panelist information from sparse flavour survey data. One component of the framework executes genetic programming ensemble based s...
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
In this paper we introduce a novel approach for the thematic organization of bibliographic records that builds upon a semantic relatedness measure we have implemented for this tas...
George Tsatsaronis, Iraklis Varlamis, Sofia Stamou...
Commercial, non-profit and public organizations are accumulating huge amounts of electronically available text documents. Although composed of unstructured texts, documents contai...