Implementation of a multi-objective genetic algorithm on word segmentation in modern Greek
Zacharias Detorakis, George Tambouratzis · International Conference on Artificial Intelligence and Soft Computing · 2007
A genetic algorithm (GA) is presented in this article aiming at the automated extraction of morphological information from a corpus and ultimately at the creation of a computational model capable of distinguishing the stem of a word from its inflectional suffix. A multiobjective approach of a GA (MGA) is introduced, where different objective functions are used for the selection of each parent that participates in the reproduction operation of the GA. The system is presented with a training corpus, and subsequently used to segment a different test corpus. The effect that various parameters, relevant to the GA, have on the performance of the system is examined and conclusions are drawn on their optimum values.