In this work, a genetic word clustering algorithm, that classifies words present in the phrases of a linguistic corpus, is proposed. The underlying goal of word classification is to build a good probabilistic model of the language defined by the phrases in the corpus. Some experiments comparing the performance of the proposed algorithm with a classical word clustering algorithm were carried out.
