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Natural language processing is a field within artificial intelligence that studies how to computationally model human language. The representation of words through vectors, known as Word embedding, has become popular in recent years through techniques such as Doc2Vec or Word2Vec. This study evaluates the use of Doc2Vec in a set of conversations collected by ECU911 emergency center. The purpose was to classify incidents, consequently the operator is able to make the best decision regarding the actions to be taken when an emergency occurs. The data were recorded during 2020, in the emergency center located in Cuenca, Ecuador. In addition, Doc2Vec was compared with the Word2Vec technique to verify its performance level both in terms of accuracy and time. Based on the tests performed, it was concluded that Doc2Vec has a solid performance when using trained models with large corpus, outperforming Word2Vec.
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