Accurate and reliable visualization of blood vessels is still a challenging problem, notably in
the presence of morphologic changes resulting from atherosclerotic diseases. We take …

Motivation: A model for learning potential causes of toxicity from positive and negative
examples and predicting toxicity for the dataset used in the Predictive Toxicology Challenge …

This paper describes a multi-dimensional knowledge discovery and data mining (KDD)
methodology that aims at discovering actionable knowledge related to Internet threats …

One of the most fundamental models for cohesive subgraph mining in network analysis is
that which involves the use of cliques. In bipartite graph analysis, the detection of maximal …

The main topic of this thesis is knowledge discovery in databases (KDD). More precisely, we
have investigated two of the most important tasks of KDD today, namely itemset extraction …

This article presents the method Wave Top-k Random-d Lineage Search (WaveLSea) which
guides an expert through data mining results according to her interest. The method exploits …

We discuss the issues involved in controlling computer applications via gestures composed
of both static symbols and dynamic motions. Each gesture is modeled from either static …

We study algorithms to compute the Shapley value for a cooperative game on a lattice L
Σ=(F Σ,⊆) where F Σ is the family of closed sets given by an implicational system Σ on a set …

In this chapter, we present a smooth introduction to symbolic methods for knowledge
discovery in databases (KDD). The KDD process extracts from large databases information …

We investigate the complexity of enumerating pseudo-intents in the lectic order. We look at
the following decision problem: Given a formal context and a set of n pseudo-intents …