Burghard B. Rieger:
In: Wang, Paul P. (ed.): Computing with Words. New York (John Wiley & Sons) 2001, pp.147-208
The notion of Computing with Words (CW) hinges crucially on the employment of natural language expressions. These are considered observable and accessible evidence of processes of human cognition, represented by textual structures and actualized in processes of understanding. Cognitive processes and language structures are characterized by information granulation, organization and causation which can be modeled both, in their crisp as well as fuzzy modes of structural representation and functional processing.
In a rather sharp departure from AI and CL approaches, modeling in Computational Semiotics (CS) as based on Fuzzy Linguistics (FL) neither presupposes rule-based or symbolic formats for linguistic knowledge representations, nor does it subscribe to the notion of world knowledge as some static structures that may be abstracted from and represented independently of the way they are processed. Consequently, knowledge structures and the processes operating on them are modeled procedurally and implemented as algorithms. They determine Semiotic Cognitive Information Processing (SCIP) systems as collections of information processing devices whose semiotic character consists in a multi-level representational system of working structures emerging from and being modified by such processing. For dynamic cognitive models of natural language understanding, the systems theoretical view suggests to accept natural language discourse as multi-resolutionally structured results of semiotic processes. As such they become empirically accessible and allow for mutual analyses by tracing observable structures back to their constitutive processes and vice versa.
To show the approach's feasibility, examples of soft linguistic categorizing as well as results of dynamic meaning constitution will be derived formally and also computed from discourse data. The new entities' employment will be illustrated by a number of procedures whose properties are discussed as implemented to realize-rather than simulate-language understanding by machine as a semiotic enactment of meaning constitution.
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