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
Abstract
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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