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Functional features are investigated and shortcomings in the existing process of sending messages about city problems on the “Our St. Petersburg” portal are revealed. The approach to automatic classification development of citizens ' messages by existing on portal categories is described. Based on reports submitted by citizens in the amount of 1.5 million, training and test samples were formed in the ratio of 80% and 20% of texts main volume, respectively. Based on training data sample and 194 categories, the algorithm of automatic classification was trained using such classical methods of machine learning as naive Bayes classifier, decision trees and artificial neural networks. Using the method of determining effectiveness of the classification and test sample, trained algorithm was tested and checked. The analysis revealed that algorithm based on the use of artificial neural networks shows the best result among the other methods used. The average classification accuracy of the algorithm was approximately 82%. The trained algorithm was used in the development of an intellectual classifier, which is a web application and implements API mechanisms for interaction with main modules of the portal information system.

Intellectual classifier development of citizens' messages on the «Our St. Petersburg» portal: experience in using machine learning methods