Asymptotic Time Complexity of Identification of Basic-level

Abstract

Abstract Introduction This paper focuses on cognitive computing approaches to identifying the basic-level in a hierarchical structure. In particular, it provides asymptotic time complexities of the identification of the basic-level for five basic-levelness measures, i.e., feature-possession, category utility, category attentional slip, category’s cue validity with global threshold, category’s cue validity with feature-possession. Methods Asymptotic time complexities were analytically determined for each basic-levelness measure separately. Results First, the time complexity of auxiliary measures (i.e., utilized by basic-levelness measures) was determined. Second, the time complexity of the identification of the basic-level was determined. Finally, an optimization of the identification was proposed. Conclusions The identification of the basic-level requires polynomial time. In particular, category attentional slip and category’s cue validity with feature-possession require an additional iteration through all objects, which increase the time complexity.