{"title":"电子档案文档的本体模型","authors":"A. Zarubin, A. Koval, V. Moshkin","doi":"10.1145/3397056.3397065","DOIUrl":null,"url":null,"abstract":"The task of semantic structuring and extracting the necessary knowledge from large electronic archives when making management decisions is very urgent. This work presents an ontological model of a project document and an algorithm for classifying a large amount of unstructured information in an electronic archive. The work also presents the results of experiments on data from the electronic archive of the Federal Scientific and Practical Center MARS. The experimental results show the effectiveness of the developed models and algorithms.","PeriodicalId":365314,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ontological Model of an Electronic Archive Document\",\"authors\":\"A. Zarubin, A. Koval, V. Moshkin\",\"doi\":\"10.1145/3397056.3397065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The task of semantic structuring and extracting the necessary knowledge from large electronic archives when making management decisions is very urgent. This work presents an ontological model of a project document and an algorithm for classifying a large amount of unstructured information in an electronic archive. The work also presents the results of experiments on data from the electronic archive of the Federal Scientific and Practical Center MARS. The experimental results show the effectiveness of the developed models and algorithms.\",\"PeriodicalId\":365314,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3397056.3397065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3397056.3397065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontological Model of an Electronic Archive Document
The task of semantic structuring and extracting the necessary knowledge from large electronic archives when making management decisions is very urgent. This work presents an ontological model of a project document and an algorithm for classifying a large amount of unstructured information in an electronic archive. The work also presents the results of experiments on data from the electronic archive of the Federal Scientific and Practical Center MARS. The experimental results show the effectiveness of the developed models and algorithms.