{"title":"通过应用程序的使用来识别开发人员","authors":"Ihar Shulhan","doi":"10.1109/ICSE-Companion.2019.00070","DOIUrl":null,"url":null,"abstract":"In this paper we propose and evaluate a method based on recurrent neural networks to identify users by their application usage. The method was tested on the data collected by non-invasive metrics collection system developed at Innopolis University. The first results achieved on initial dataset show a high user identification accuracy and a potential for further research.","PeriodicalId":273100,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Developers by Their Application Usage\",\"authors\":\"Ihar Shulhan\",\"doi\":\"10.1109/ICSE-Companion.2019.00070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose and evaluate a method based on recurrent neural networks to identify users by their application usage. The method was tested on the data collected by non-invasive metrics collection system developed at Innopolis University. The first results achieved on initial dataset show a high user identification accuracy and a potential for further research.\",\"PeriodicalId\":273100,\"journal\":{\"name\":\"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSE-Companion.2019.00070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSE-Companion.2019.00070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we propose and evaluate a method based on recurrent neural networks to identify users by their application usage. The method was tested on the data collected by non-invasive metrics collection system developed at Innopolis University. The first results achieved on initial dataset show a high user identification accuracy and a potential for further research.