{"title":"武汉开发岗位招聘的数据挖掘设计","authors":"Q. Miao","doi":"10.1109/ISAIAM55748.2022.00028","DOIUrl":null,"url":null,"abstract":"Due to the important strategic position of Wuhan City and the serious brain drain and asymmetry of talent recruitment information in Wuhan, this paper, from the perspective of data mining, takes the recruitment information of development positions in Wuhan published on lagou.com as the research data, using the C5.0 decision tree model and Bayesian network model for classification prediction, predicting the importance of variables, and generating some prediction rule sets to help job seekers and recruiters in the IT field to match job intentions and job requirements. The model evaluation results show that the use of decision tree model and Bayesian network model for prediction has high reference.","PeriodicalId":382895,"journal":{"name":"2022 2nd International Symposium on Artificial Intelligence and its Application on Media (ISAIAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data mining design for development job recruitment in Wuhan\",\"authors\":\"Q. Miao\",\"doi\":\"10.1109/ISAIAM55748.2022.00028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the important strategic position of Wuhan City and the serious brain drain and asymmetry of talent recruitment information in Wuhan, this paper, from the perspective of data mining, takes the recruitment information of development positions in Wuhan published on lagou.com as the research data, using the C5.0 decision tree model and Bayesian network model for classification prediction, predicting the importance of variables, and generating some prediction rule sets to help job seekers and recruiters in the IT field to match job intentions and job requirements. The model evaluation results show that the use of decision tree model and Bayesian network model for prediction has high reference.\",\"PeriodicalId\":382895,\"journal\":{\"name\":\"2022 2nd International Symposium on Artificial Intelligence and its Application on Media (ISAIAM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Symposium on Artificial Intelligence and its Application on Media (ISAIAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAIAM55748.2022.00028\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Symposium on Artificial Intelligence and its Application on Media (ISAIAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAIAM55748.2022.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data mining design for development job recruitment in Wuhan
Due to the important strategic position of Wuhan City and the serious brain drain and asymmetry of talent recruitment information in Wuhan, this paper, from the perspective of data mining, takes the recruitment information of development positions in Wuhan published on lagou.com as the research data, using the C5.0 decision tree model and Bayesian network model for classification prediction, predicting the importance of variables, and generating some prediction rule sets to help job seekers and recruiters in the IT field to match job intentions and job requirements. The model evaluation results show that the use of decision tree model and Bayesian network model for prediction has high reference.