How evolutionary algorithms are applied to statistical natural language processing.
Lourdes Araujo.
Artificial Intelligence Review. 28(4), (2007). p. 275-303.

Statistical natural language processing (NLP) and evolutionary algorithms (EAs) are two
very active areas of research which have been combined many times. In general, statistical
models applied to deal with NLP tasks require designing specific algorithms to be trained and
applied to process new texts. The development of such algorithms may be hard. This makes EAs
attractive since they offer a general design, yet providing a high performance in particular
conditions of application. In this article, we present a survey of many works which apply EAs to
different NLP problems, including syntactic and semantic analysis, grammar induction, summaries and
text generation, document clustering and machine translation. This review finishes extracting
conclusions about which are the best suited problems or particular aspects within those problems
to be solved with an evolutionary algorithm.