Fuzzy Computational Semantics

Other than clear-cut symbolic representational formats employed sofar in natural language processing by machine, it is argued here, that fuzzy distributional representations correspond directly to the way word meanings are constituted and understood by (natural and artiicial) information processing systems. Based upon such systems' theoretical performance in general and the pragmatics of communicative interaction by real language users in particular, the notions of situation and language game as introduced by Barwise/Perry and Wittgenstein respectively are combined to allow for a numerical reconstruction of processes that simulate the constitution of meaning and the interpretation of signs. This is achieved by modelling the linear or syn-tagmatic and selective or paradigmatic constraints which natural language structure imposes on the formation of (strings of) linguistic entities. A formalism with related algorithms and test results of their implementation are produced in order to substantiate the claim for a model of a semiotic cognitive information processing system (SCIPS) that operates in a linguistic environment as some meaning acquisition and understanding device. 1 The semiotic background For researchers in knowledge representation and natural language semantics graph-theoretical formats have become standard representational means to deal with meaning , both as relational structure and denotational reference. Relating arc-and-node 1 Rieger: Fuzzy Computational Semantics 2 structures with sign-and-term labels in formats like trees and nets is but another aspect of the traditional mind-matter-duality according to which a realm of meanings is presupposed very much like the assumption of the pregiven structures of the real world that can be related to signs. Accepting this duality will neither allow to explain where the structures nor where the labels come from the relation of which is understood to represent meanings. Their emergence, therefore, never occurred to be in need of some explanatory modelling because the existence of objects, signs and meanings were taken for granted and hence seemed to be out of all scrutiny. Under this presupposition, fundamental semiotic questions of semantics simply did not come up, they have hardly been asked yet, and are still far from being solved. 1 discern three categories of modelling cognition: the cognitivistic approach presupposes the existence of the external world, struc-tured by given objects and properties the internal representations of which are to be used by cognitive systems in order to act and react; the emergent approach is described as based on the model concept of self-organization with the cognitive system constantly adapting to changing environmental …