{"title":"Big Data Mining Algorithm of Internet of Things Based on Artificial Intelligence Technology","authors":"W. Li","doi":"10.1109/ISAIEE57420.2022.00032","DOIUrl":null,"url":null,"abstract":"According to the low accuracy of big data analysis and clustering of the Internet of Things at present, this paper proposes an AI based big data mining method for the Internet of Things. By establishing the dimension control mechanism, the data pattern tree of the Internet of Things is generated, and the data mining scope is initially obtained. The data that meet the requirements are detected according to big data information, and the standardized processing is completed for the clustered feature data. Finally, data mining results are obtained by using neural network technology. The experimental results show that the F -measure value can be increased by 15.01 % and 17.52%, and the RI value can be increased by 20.32% and 25.03%. The clustering accuracy of the algorithm is obviously improved.","PeriodicalId":345703,"journal":{"name":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAIEE57420.2022.00032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
According to the low accuracy of big data analysis and clustering of the Internet of Things at present, this paper proposes an AI based big data mining method for the Internet of Things. By establishing the dimension control mechanism, the data pattern tree of the Internet of Things is generated, and the data mining scope is initially obtained. The data that meet the requirements are detected according to big data information, and the standardized processing is completed for the clustered feature data. Finally, data mining results are obtained by using neural network technology. The experimental results show that the F -measure value can be increased by 15.01 % and 17.52%, and the RI value can be increased by 20.32% and 25.03%. The clustering accuracy of the algorithm is obviously improved.