Automatic Detection of Semantic Primitives with Bio-inspired, Multi-Objective, Weighting Algorithms

This paper proposes the usage of computational techniques that allow for automatic analysis of the vocabulary contained in an explanatory dictionary. It is proposed for the extraction of a set of words, called semantic primitives, which are considered those allowing the creation of a system used to establish definitions in dictionaries. The proposed approach is based on the representation of a dictionary as a directed graph and the combination of a multi-objective differential evolution algorithm with the PageRank weighting algorithm. The differential evolution algorithm extracted a set of primitives that fulfill two objectives: minimize the set size and maximize its degree of representation (PageRank), allowing the creation of a computational dictionary without cycles in its definitions. We experimented with a RAE dictionary of Spanish. Our results present improvement over other algorithms that are representative of the state-of-the-art.