A New Approach to the POS Tagging Problem Using Evolutionary Computation

The purpose of part-of-speech tagging is to automatically tag the words of a text, written in a certain language, with labels that usually take the form of acronyms that designate the appropriate parts-of-speech. In this paper we propose a new approach to the problem that divides it in two different tasks: a learning task and an optimization task. We tackled each of those tasks with evolutionary computation techniques: genetic algorithms and a particle swarm optimizer. We emphasize the use of swarm intelligence, not only for the good results achieved, but also because it is one of the first applications of such algorithms to this problem. We believe that this approach is generic enough so that it can be though as an alternative approach to solve other natural language processing tasks that share some fundamental characteristics with the part-of-speech tagging problem. The results obtained in two different English corpora are among the best published ones.