{"title":"物联网环境下快速数据分析的近似迭代法","authors":"Yong-Ju Lee, Ok-Gee Min","doi":"10.1109/ICISSEC.2016.7885844","DOIUrl":null,"url":null,"abstract":"Fast data (the next step after big data) revolution leads to new requirements in data processing platforms. To overcome the fast data bottleneck caused by data in extremely rapid transit, adaptive data approximation is one of the alternative ways to handle incredible data speed. In this paper, we present an approximate iterative method for fast data analysis and investigate what benefits and opportunities might be available in Internet of Things environment.","PeriodicalId":420224,"journal":{"name":"2016 International Conference on Information Science and Security (ICISS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approximate Iterative Method for Fast Data Analysis in Internet of Things Environment\",\"authors\":\"Yong-Ju Lee, Ok-Gee Min\",\"doi\":\"10.1109/ICISSEC.2016.7885844\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fast data (the next step after big data) revolution leads to new requirements in data processing platforms. To overcome the fast data bottleneck caused by data in extremely rapid transit, adaptive data approximation is one of the alternative ways to handle incredible data speed. In this paper, we present an approximate iterative method for fast data analysis and investigate what benefits and opportunities might be available in Internet of Things environment.\",\"PeriodicalId\":420224,\"journal\":{\"name\":\"2016 International Conference on Information Science and Security (ICISS)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Information Science and Security (ICISS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISSEC.2016.7885844\",\"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 International Conference on Information Science and Security (ICISS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISSEC.2016.7885844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximate Iterative Method for Fast Data Analysis in Internet of Things Environment
Fast data (the next step after big data) revolution leads to new requirements in data processing platforms. To overcome the fast data bottleneck caused by data in extremely rapid transit, adaptive data approximation is one of the alternative ways to handle incredible data speed. In this paper, we present an approximate iterative method for fast data analysis and investigate what benefits and opportunities might be available in Internet of Things environment.