Data Mining

In the domain of data mining, the research activity primarily focused on two questions: firstly, how data mining algorithms can benefit from knowledge representation systems, and secondly, how the efficiency of existing systems can be improved. A first important contribution in this work consisted in the formalization and the implementation of a knowledge representation language that was scalable enough to be used in conjunction with data mining tools. A very efficient system based on a relational database system and a sophisticated query language was designed and implemented. The principal data mining tasks performed by the system were high level classification rule induction, indexing and grouping. A second contribution is a deep analyse of the criterion used during the construction of a decision tree, which conducted to a new family of split functions with better performance on large data sets than classical split functions.  And a third contribution consists in the formalization of a general framework for temporal data mining which also capture uncertainty aspects of knowledge.