Complexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic fr...
Knowledge in knowledge bases have two categories: complete and incomplete. In this paper, through uniformly expressing these two kinds of knowledge, we first address four operator...
Many applications of knowledge discovery require the knowledge to be consistent with data. Examples include discovering rules for query optimization, database integration, decisio...
In this paper we introduce our departments organizational and technical infrastructure for knowledge-intensive and weak-structured processes: A framework for Knowledge Management ...
Knowledge Discovery in Databases (KDD), also known as data mining, focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns wi...
This paper stresses the contribution of the process of knowledge discovery in databases for the effective creation and sharing of organizational knowledge. The focus on the proces...
The Grid is the computing and data management infrastructure, which is transforming science, business, health and society. This paper deals with a challenging task addressing know...
We present a novel approach to describe the knowledge discovery process, focusing on a generalized form of attribute called view. It is observed that the process of knowledge disc...
In this paper, we present research trends carried out in the Orpailleur team at loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge disco...
Jean Lieber, Amedeo Napoli, Laszlo Szathmary, Yann...
Exploratory data mining is fundamental to fostering an appreciation of complex datasets. For large and continuously growing datasets, such as obtained by regular sampling of an or...