Word Similarity Perception: an Explorative Analysis

Natural language is a medium for expressing things belonging to conceptual and cognitive levels, made of words and grammar rules used to carry semantics. However, its natural ambiguity is the main critical issue that computational systems are generally asked to solve. In this paper, we propose to go beyond the current conceptualization of word similarity, i.e., the building block of disambiguation at computational level. First, we analyze the origin of the perceived similarity, studying how conceptual, functional, and syntactic aspects influence its strength. We report the results of a two-stages experiment showing clear similarity perception patterns. Then, based on the insights gained in the cognitive tests, we developed a computational system that automatically predicts word similarity reaching high levels of accuracy.