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The article presents a method that improves the quality of classification ofobjects described by a combination of known and unknown features. The method isbased on modernized Informational Neurobayesian Approach with consideration ofunknown features. The proposed method was developed and trained on 1500 textqueries of Promobot users in Russian to classify them into 20 categories(classes). As a result, the use of the method allowed to completely solve theproblem of misclassification for queries with combining known and unknownfeatures of the model. The theoretical substantiation of the method ispresented by the formulated and proved theorem On the Model with LimitedKnowledge. It states, that in conditions of limited data, an equal number ofequally unknown features of an object cannot have different significance forthe classification problem.

Neural Network-based Object Classification by Known and Unknown Features (Based on Text Queries)