Object classification using basic-level categories

This paper introduces a computational solution allowing an artificial system to organise large datasets into a set of known basic-level categories. Following cognitive computing paradigm we present an approach towards category-based internal organisation of cognitive agent's semantic memory. In particular, assuming a given set of basic-level categories (predefined or developed) we provide a concise introduction to two perceptron-based computational models allowing an artificial system to classify objects into basic-level categories. Utilising results from other disciplines (psychology, linguistics and cognitive science) we take advantage of the notion of cue validity and incorporate it as underlying weights of input features. Finally, using real bird species dataset we highlight simulation results of classification's precision and recall measures.