Classification of short texts using a wave model
https://doi.org/10.17586/2226-1494-2022-22-2-287-293
Abstract
Quantum computing algorithms are actively developed and applied in the field of natural language processing. The authors of the paper proposed a new quantum-like method for classifying short texts. The basis of the method is the representation of the text as an ensemble of elementary particles. The value of the detection probability amplitude of a given ensemble at the selected points in space is chosen as a classification criterion. In this case, the space is understood as a vector space described using the distributive-semantic model of the language. The authors suggested one of the possible ways of interpreting the parameters of the wave function that describes the behavior of an elementary particle, as well as an algorithm for calculating the probability amplitude taking into account these parameters. For the experimental research of the described method, authors performed the classification of Internet communities by topics. For the analysis, the names and the “information” section of communities were used. In total, 100 groups of the social network “VKontakte” belonging to five various topics were taken. The proposed model showed rather high classification accuracy (91 % in general on the data set and from 75 % to 95 % within individual classes). The proposed model is supposed to be used to classify user comments about goods, services and events, as well as to determine some properties of the psychological portraits of users of online communities.
Keywords
classification,
natural language processing,
wave model,
interference,
quantum-like model,
definition of the text subject
Supporting agencies: The work was carried out within the framework of the project No. 620164 (artificial intelligence methods for cyberphysical systems).
About the Authors
A. S. Gruzdeva
ITMO University
Russian Federation
Russian Federation
Anastasia S. Gruzdeva — PhD student
Saint Petersburg, 197101
I. A. Bessmertny
ITMO University
Russian Federation
Russian Federation
Igor A. Bessmertny — D.Sc., Full Professor
Saint Petersburg, 197101
sc 36661767800
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Review
For citations:
Gruzdeva A.S., Bessmertny I.A. Classification of short texts using a wave model. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2022;22(2):287-293. (In Russ.) https://doi.org/10.17586/2226-1494-2022-22-2-287-293
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