Jörg-Uwe Kietz

Extracting a domain-specific ontology from a corporate intranet

This paper describes our actual and ongoing work in supporting semi-automatic ontology acquisition from a corporate intranet of an insurance company. A comprehensive architecture and a system for semi-automatic ontology acquisition supports processing semi-structured information (e.g. contained in dictionaries) and natural language documents and including existing core ontologies (e.g. GermaNet, WordNet). We present a method for acquiring a application-tailored domain ontology from given heterogeneous intranet sources.

M 4 : a metamodel for data preprocessing

Metadata-driven tools store control information in repositories that are outside of programs and applications. At runtime, this control information (i.e., metadata) is read, interpreted and dynamically bound into software execution. If new requirements arise, metadata may be changed without affecting the programs sharing it and without requiring re-compilation of these programs. Repositories store metadata according to a metadata structure, called a metamodel. M4 is the metamodel used by Mining Mart, a system for supporting data preprocessing for data mining. The aim of this paper is twofold. First, we introduce M4 (the MetaModel of Mining Mart) and present some ideas underlying the design and implementation. Second, we discuss on the basis of M4 issues related to metadata-driven software: advantages of building and using such software, its weaknesses and the role it plays for metadata management, especially within data warehousing environments.