Connectionist Modeling of Linguistic Quantifiers

R.K. Rajapakse, A. Cangelosi, K.R. Coventry, S. Newstead, A. Bacon

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

This paper presents a new connectionist model of the grounding of linguistic quantifiers in perception that takes into consideration the contextual factors affecting the use of vague quantifiers. A preliminary validation of the model is presented through the training and testing of the model with experimental data on the rating of quantifiers. The model is able to perform the “psychological” counting of objects (fish) in visual scenes and to select the quantifier that best describes the scene, as in psychological experiments.
Original languageEnglish
Title of host publicationArtificial Neural Networks: Formal Models and Their Applications
EditorsW Duch, J Kacprzyk, E Oja, S Zadrozny
Place of PublicationBerlin Heidelberg
PublisherSpringer
Pages679-684
Number of pages6
Volume3697
ISBN (Print)978-3540287551
DOIs
Publication statusPublished - 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3697

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