Abstract
This work introduces a framework that implements asymmetric communication theory proposed by Sperber and Wilson [1]. The framework applies a generalization model known as the Bayesian model of generalization (BMG) [2] for aligning knowledge possessed by two communicating parties. The work focuses on the application of the BMG to publicly available datasets, the Leuven natural concept database [3] representing semantic structures of domain knowledge possessed by individual subjects [3]. Results indicate that the BMG is potentially a model applicable to simulating the alignment of domain knowledge from the information receiver’s viewpoint.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference23 articles.
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