Mano Ashish Tripathi, Elizabeth Chacko, J. V., Aditi Srivastava, Shaik Rehana Banu, V. Dwivedi
{"title":"基于模糊数据挖掘算法的电力行业人力资源管理","authors":"Mano Ashish Tripathi, Elizabeth Chacko, J. V., Aditi Srivastava, Shaik Rehana Banu, V. Dwivedi","doi":"10.1109/ACCAI58221.2023.10200599","DOIUrl":null,"url":null,"abstract":"Currently, database and information technology's frontier study area is data mining. It is acknowledged as one of the essential technologies with the greatest potential. Numerous technologies with a comparatively high level of technical substance are used in data mining, including artificial intelligence, neural networks, fuzzy theory, and mathematical statistics. The realization is challenging as well. Job satisfaction is one of several factors that cause employees to leave or switch jobs, and it is also closely tied to the organization's human resource management (HRM) procedures. It is continuously difficult and at times beyond the HR office's control to keep their profoundly qualified and talented specialists, yet data mining can assume a part in recognizing those labourers who are probably going to leave an association, permitting the HR division to plan a mediation methodology or search for options. We have analysed the major thoughts, techniques, and calculations of affiliation rule mining innovation in this article. They effectively finished affiliation broadcasting, acknowledged perception, and eventually revealed valuable data when they were coordinated into the human resource management arrangement of schools and colleges.","PeriodicalId":382104,"journal":{"name":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human Resource Management in the Power Industry Using Fuzzy Data Mining Algorithm\",\"authors\":\"Mano Ashish Tripathi, Elizabeth Chacko, J. V., Aditi Srivastava, Shaik Rehana Banu, V. Dwivedi\",\"doi\":\"10.1109/ACCAI58221.2023.10200599\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, database and information technology's frontier study area is data mining. It is acknowledged as one of the essential technologies with the greatest potential. Numerous technologies with a comparatively high level of technical substance are used in data mining, including artificial intelligence, neural networks, fuzzy theory, and mathematical statistics. The realization is challenging as well. Job satisfaction is one of several factors that cause employees to leave or switch jobs, and it is also closely tied to the organization's human resource management (HRM) procedures. It is continuously difficult and at times beyond the HR office's control to keep their profoundly qualified and talented specialists, yet data mining can assume a part in recognizing those labourers who are probably going to leave an association, permitting the HR division to plan a mediation methodology or search for options. We have analysed the major thoughts, techniques, and calculations of affiliation rule mining innovation in this article. They effectively finished affiliation broadcasting, acknowledged perception, and eventually revealed valuable data when they were coordinated into the human resource management arrangement of schools and colleges.\",\"PeriodicalId\":382104,\"journal\":{\"name\":\"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACCAI58221.2023.10200599\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACCAI58221.2023.10200599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human Resource Management in the Power Industry Using Fuzzy Data Mining Algorithm
Currently, database and information technology's frontier study area is data mining. It is acknowledged as one of the essential technologies with the greatest potential. Numerous technologies with a comparatively high level of technical substance are used in data mining, including artificial intelligence, neural networks, fuzzy theory, and mathematical statistics. The realization is challenging as well. Job satisfaction is one of several factors that cause employees to leave or switch jobs, and it is also closely tied to the organization's human resource management (HRM) procedures. It is continuously difficult and at times beyond the HR office's control to keep their profoundly qualified and talented specialists, yet data mining can assume a part in recognizing those labourers who are probably going to leave an association, permitting the HR division to plan a mediation methodology or search for options. We have analysed the major thoughts, techniques, and calculations of affiliation rule mining innovation in this article. They effectively finished affiliation broadcasting, acknowledged perception, and eventually revealed valuable data when they were coordinated into the human resource management arrangement of schools and colleges.