{"title":"JSM推理应用于新冠肺炎被测者数据的结果分析","authors":"E. A. Efimova","doi":"10.3103/S0005105522060024","DOIUrl":null,"url":null,"abstract":"<p>The paper describes the results of JSM reasoning applied to COVID-19 testees’ data formed from their symptoms. We construct graphs of objects and hypotheses and consider stable sets of vertices. We also find all minimal subsets of those testees who have recovered from COVID-19 and collectively have all groups of symptoms that are possible signs of the disease, as well as all minimal sets of subgroups of symptoms such that all recovered testees collectively have.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analysis of Results of JSM Reasoning Applied to Covid-19 Testees’ Data\",\"authors\":\"E. A. Efimova\",\"doi\":\"10.3103/S0005105522060024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The paper describes the results of JSM reasoning applied to COVID-19 testees’ data formed from their symptoms. We construct graphs of objects and hypotheses and consider stable sets of vertices. We also find all minimal subsets of those testees who have recovered from COVID-19 and collectively have all groups of symptoms that are possible signs of the disease, as well as all minimal sets of subgroups of symptoms such that all recovered testees collectively have.</p>\",\"PeriodicalId\":42995,\"journal\":{\"name\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.3103/S0005105522060024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105522060024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Analysis of Results of JSM Reasoning Applied to Covid-19 Testees’ Data
The paper describes the results of JSM reasoning applied to COVID-19 testees’ data formed from their symptoms. We construct graphs of objects and hypotheses and consider stable sets of vertices. We also find all minimal subsets of those testees who have recovered from COVID-19 and collectively have all groups of symptoms that are possible signs of the disease, as well as all minimal sets of subgroups of symptoms such that all recovered testees collectively have.
期刊介绍：
Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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