Accession Number : ADA214326

Title :   A Structured Connectionist Approach to Direct Inferences and Figurative Adjective-Noun Combinations.

Descriptive Note : Doctoral thesis,

Corporate Author : ROCHESTER UNIV NY DEPT OF COMPUTER SCIENCE

Personal Author(s) : Weber, Susan H.

Report Date : MAY 1989

Pagination or Media Count : 182

Abstract : This work was motivated by the observation that categories have internal structure sufficiently sophisticated to capture a variety of effects, ranging from the direct inferences arising from adjectival modification of nouns to the ability to comprehend figurative usages. The design of the internal structure of category representation is constrained by the model requirements of the connectionist implementation and by the observable behaviors exhibited in direct inferences. The former dictates the use of a spreading activation format, and the latter indicates some to the topology and connectivity of the resultant semantic network. The connectionist knowledge representation scheme described in this thesis is based on the idea that categories and concepts are context sensitive and functionally structured. Each functional property value of a category motivates a distinct aspect of that category's internal structure. This model of cognition, as implemented in a structured connectionist knowledge representation system, permits the system to draw immediate inferences, and, when augmented with property inheritance mechanisms, mediated inferences about the full meaning of adjective-noun combinations. These inferences are used not only to understand the implicit references to correlated properties (a green peach is unripe) but also to make sense of figurative adjective uses, by drawing on the connotations of the adjective in literal contexts. (kr)

Descriptors :   *COMPUTER PROGRAMMING, *SYSTEMS APPROACH, ACTIVATION, BEHAVIOR, COGNITION, FORMATS, INTERNAL, MODELS, NETWORKS, REQUIREMENTS, SEMANTICS, TOPOLOGY, WORDS(LANGUAGE).

Subject Categories : Computer Programming and Software

Distribution Statement : APPROVED FOR PUBLIC RELEASE