{"title":"ANALYSIS OF THE EFFECTIVENESS OF APPLYING THE FREQUENCY-CONTEXT CLASSIFICATION ALGORITHM TO TEXTS OF DIFFERENT STYLES","authors":"M. Chaika, I. Buneev, V. Velichko","doi":"10.34220/mamsp_174-178","DOIUrl":null,"url":null,"abstract":"This article discusses the application of the frequency-context classification algorithm to texts of various styles. The main features of different styles that affect the efficiency of the algo-rithm are highlighted. It is proved that the method of selecting the subject of the text using the fre-quency-context classification algorithm works best in relation to scientific and legal documents and, in its current form, is practically inapplicable for literary texts. This makes the task of modifying the algorithm to determine the subject of literary texts relevant.","PeriodicalId":113054,"journal":{"name":"Materials of the All-Russian Scientific and Practical Conference \"Modern aspects of modeling systems and processes\"","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials of the All-Russian Scientific and Practical Conference \"Modern aspects of modeling systems and processes\"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34220/mamsp_174-178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This article discusses the application of the frequency-context classification algorithm to texts of various styles. The main features of different styles that affect the efficiency of the algo-rithm are highlighted. It is proved that the method of selecting the subject of the text using the fre-quency-context classification algorithm works best in relation to scientific and legal documents and, in its current form, is practically inapplicable for literary texts. This makes the task of modifying the algorithm to determine the subject of literary texts relevant.
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