Data Mining and Knowledge Discovery for Databases Activity

The R&D efforts of the DM/KDD activity are focusing towards four directions aiming to expose the utility of data-mining in the respective disciplines and application areas. These are: (a) Introduction, design and development of novel and prototypical DM/KDD methods, techniques, algorithms, tools and systems, (b) Intelligent analysis approaches, based on DM/KDD techniques, for the recognition of genes (promoters) in DNA sequences, and Intelligent analysis of microarray/gene-expression data for the discovery of molecular markers (i.e., gene-markers) based on classification approaches, and the discovery of families of co-regulated genes (metagenes) based on clustering approaches. (c) Design of methodologies and development of algorithms, tools and systems for mining distributed and heterogeneous clinical data sources. The aim is to add intelligent capabilities into the integrated electronic healthcare record (I-EHR) towards internet-based epidemiology (d) Design and development of techniques, algorithms, systems and tools for the automated indexing of Web-documents, the automated construction of controlled-vocabularies (CV) and concept hierarchies (CH).

DM/KDD Activity Leader: Giorgos Potamias