- Faculty of Computer Science
Research group KMD
Knowledge Management & Discovery in Information Systems
c/o Henner Graubitz
DIAsDEM aims at using information being hidden in unstructured data in order to support sense-making processes. This information is mostly included in insufficiently documented data sources. Some of these sources are erroneous, incomplete or contradictory. Data mining is used to comprehend the semantics of this information and to consolidate them in an information system of integrated and reliable data for further analyses and enquiries. In this connection tasks are in particular as follows:
# Detection of semantic characteristics of data and possibly existent dependencies between semantically related data.
# Utilisation of discovered semantics for the integration of data in a homogeneous information system.
Prof. Dr. Spiliopoulou's team is mainly dealing with the extraction of semantic characteristics from application-specific text archives by methods of data mining. At this stage, more information concerning DIAsDEM can either be found in the project application (Postscript-File, PDF-File) or in our recent publications.
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