Decision Support for Qualitative Data Analysis — KEE Shell Linked to FORTRAN Programs —
For the development of a knowledge-based system for a well established application domain it is often necessary to integrate knowledge representation as well as algorithmic solution techniques. For the first part, it is desirable to use the possiblities of dedicated expert system shells like the Knowledge Engineering Environment (KEE) which integrate frame and production rule languages to form hybrid representation facilities. For the second part, most application programs, i e. in our case data analysis algorithms for different problem types, have been implemented in command-oriented languages like FORTRAN etc. So, it seems natural to represent the expert knowledge (and the decision support process) in the KEE system and to access the data analysis programs (and the numerical processing capabilities) available on other computers. The experiences in interfacing two different working environments, here KEE/LISP and FORTRAN/MSDOS, as well as the technical details of an experimental implementation are discussed.
Unable to display preview. Download preview PDF.
- Barthélemy JP, Monjardet B (1988) The Median Procedure in Data Analysis: New Results and Open Problems, to appear in: Bock HH (ed.) Proceedings of the First Conference of the International Federation of Classification Societies. North-Holland, AmsterdamGoogle Scholar
- Leclerc B (1988) Concensus Applications in the Social Sciences, to appear in: Bock HH (ed.) Proceedings of the First Conference of the International Federation of Classification Societies. North-Holland, AmsterdamGoogle Scholar
- Minsky M (1975) A Framework for Representing Knowledge, in: Winston PH (ed.) The Psychology of Computer Vision, McGraw-Hill, New York, pp 211–277Google Scholar
- Schader M (1978) Anordnung und Klassifikation von Objekten bei qualitativen Merkmalen. Anton Hain, Meisenheim/GlanGoogle Scholar
- Schader M, Tüshaus U (1986) Subgradient Methods for Analyzing Qualitative Data, in: Gaul W, Schader M (eds.) Classification as a Tool of Research. North-Holland, Amsterdam, pp 397–403Google Scholar