Burghard B. Rieger:

Generating Dependency Structures of Fuzzy Wordmeanings in Semantic Space

In: Hattori, S./Inoue, K. (eds.): Proceedings of the XIIIth International Congress of Linguists 1982, Tokyo (CIPL) 1983, pp. 543-548


Modelling system structures of word meanings and/or world knowledge is to face the problem of their mutual and complex relatedness. Under the notion of semantic relevance and knowledge disposition this interdependency may empirically be reconstructable from natural language discourse although most approaches in linguistic semantics and artificial intelligence do not address these issues. Instead, linguists as well as experts engaged in word meaning and/or world knowledge representation still provide the necessary semantic or external world data introspectively by exploring their own competence and memory capacities to depict their findings in some semantic or conceptual structures (lists, arrays, networks, etc.).
Based upon statistical means for the empirical analysis of discourse and for the formal representation of vague word meanings in natural language texts, procedures have been devised which allow for the systematic modelling of a fragment of the lexical structure constituted by the vocabulary employed in the texts as part of the concomitantly conveyed world knowledge concerned.
Inspired by ideas from the theory of semantic memory and spreading activation in cognitive psychology, a new algorithm is presented which operates on the semantic space data to generate associative dependency structures (ADS) in the format of general (n-ary) trees. These are meant to provide the base for associative semantic inferencing algorithms to complement classical deduction processes.
This paper reports on one of the central objectives of a project in computational semantics which is supported by the Northrhine-Westphalia Ministry of Science and Research.

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