G. Dimitrov, G. Panayotova, I. Garvanov, Bychkov Os, Pavel Petrov, Angel Angelov
{"title":"高校信息系统中信息社会化搜索方法的性能分析","authors":"G. Dimitrov, G. Panayotova, I. Garvanov, Bychkov Os, Pavel Petrov, Angel Angelov","doi":"10.1109/ICAIPR.2016.7585228","DOIUrl":null,"url":null,"abstract":"In this article the effectiveness of one of the main methods for assisting the information search in large data sets is analyzed, namely the method based on the social approach. This method analyzes the behavior of multiple users when searching for information, particularly the keywords they use. Based on the obtained results, the relevant algorithms in the searching engines of the organizations can be optimized. The studies are based on data extracted from the databases of two relatively large information systems based at the University in Library Studies and Information Technologies in Sofia, Bulgaria and University of Economics in Varna, Bulgaria. The numerical and experimental results are analyzed and discussed.","PeriodicalId":127231,"journal":{"name":"2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","volume":"593 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Performance analysis of the method for social search of information in university information systems\",\"authors\":\"G. Dimitrov, G. Panayotova, I. Garvanov, Bychkov Os, Pavel Petrov, Angel Angelov\",\"doi\":\"10.1109/ICAIPR.2016.7585228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article the effectiveness of one of the main methods for assisting the information search in large data sets is analyzed, namely the method based on the social approach. This method analyzes the behavior of multiple users when searching for information, particularly the keywords they use. Based on the obtained results, the relevant algorithms in the searching engines of the organizations can be optimized. The studies are based on data extracted from the databases of two relatively large information systems based at the University in Library Studies and Information Technologies in Sofia, Bulgaria and University of Economics in Varna, Bulgaria. The numerical and experimental results are analyzed and discussed.\",\"PeriodicalId\":127231,\"journal\":{\"name\":\"2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR)\",\"volume\":\"593 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIPR.2016.7585228\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Third International Conference on Artificial Intelligence and Pattern Recognition (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIPR.2016.7585228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance analysis of the method for social search of information in university information systems
In this article the effectiveness of one of the main methods for assisting the information search in large data sets is analyzed, namely the method based on the social approach. This method analyzes the behavior of multiple users when searching for information, particularly the keywords they use. Based on the obtained results, the relevant algorithms in the searching engines of the organizations can be optimized. The studies are based on data extracted from the databases of two relatively large information systems based at the University in Library Studies and Information Technologies in Sofia, Bulgaria and University of Economics in Varna, Bulgaria. The numerical and experimental results are analyzed and discussed.