Online Trained Model of Tweets Expertise

The paper proposes a model for the examination of tweets (brief texts and messages) in Russian. The model is based on the authors' explorations on the identification of tweets meanings. The main idea is to apply the latest developed quantum machine learning method to the hierarchical classification models of texts. This approach avoids the text corpus necessity and supports the online learning due to the very design. The model proposed is tested in the experiment. The target content was given in the experiment and the model is used to measure the correspondence between the target topics and the test messages. The result of the experiment shows that the proposed method allows to distinguish the target content in the test text.