Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/36586
Title: Models and algorithms for automatic labelling of unstructured texts (text tagging)
Author(s): Shakhmametova, Gyuzel
Ishmukhametov, Ilshat
Issue Date: 2021
Language: English
Abstract: The article discusses the task of automatic labelling of texts to improve the efficiency of processing unstructured text data. An overview of existing software products for solving the problem is given, showing the need to develop its own solution specialized in the processing of Russian-language texts. The problem of assigning labels is considered from a mathematical point of view as a problem of multilabel classification, with corresponding mathematical models analysed and described. Based on this, models, algorithms, and a software product for automatically assigning labels to texts have been developed. Numerical experiments were carried out that showed the universality of the method and the possibility of application both in non-specialized and specialized fields, in particular, for processing medical documents.
URI: https://opendata.uni-halle.de//handle/1981185920/36819
http://dx.doi.org/10.25673/36586
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Appears in Collections:International Conference on Applied Innovations in IT (ICAIIT)

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