Abstract
Modeling system structures of word meanings and/or world knowledge is to face the problem of their mutual and complex relatedness. In linguistic semantics, cognitive psychology, and knowledge representation most of the necessary data concerning lexical, semantic and/or external world information is still provided introspectively. In a rather sharp departure from that form of data acquisition the present approach has been based on the empirical analysis of discourse that real speakers/writers produce in actual situations of performed or intended communication in prescriptive contexts or subject domains. The approach makes essential use of statistical means to analyze usage regularities of words to map their fuzzy meanings and connotative interrelations in a format of stereotypes. Their dependencies are generated algorithmically as multi-perspective dispositions that render only those relations accessible to automatic processing which can - under differing aspects differently — be considered relevant. Generating such semantic dispositional dependencies dynamically by a procedure would seem to be an operational prerequisitie to and a promising candidate for the simulation of contents-driven (analogically-associative), instead of formal (logically-deductive) inferences in semantic processing.
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Rieger, B.B. (1985). On Generating Semantic Dispositions in a Given Subject Domain. In: Agrawal, J.C., Zunde, P. (eds) Empirical Foundations of Information and Software Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-2521-5_23
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DOI: https://doi.org/10.1007/978-1-4613-2521-5_23
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