{"title":"Intelligent Data Analysis and its challenges in big data environment","authors":"Weichang Kong, Qidi Wu, Li Li, F. Qiao","doi":"10.1109/ICSSE.2014.6887915","DOIUrl":null,"url":null,"abstract":"Intelligent Data Analysis (IDA) is one of the most important approaches in the field of data mining, which attracts great concerns from the researchers. Based on the basic principles of IDA and the features of datasets that IDA handles, the development of IDA is briefly summarized from three aspects, i.e., algorithm principle, the scale and type of the dataset. Moreover, the challenges facing the IDA in big data environment are analyzed from four views, including big data management, data collection, data analysis, and application pattern. It is also cleared that in order to extract more values from data, the further development of IDA should combine practical applications and theoretical researches together.","PeriodicalId":166215,"journal":{"name":"2014 IEEE International Conference on System Science and Engineering (ICSSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2014.6887915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Intelligent Data Analysis (IDA) is one of the most important approaches in the field of data mining, which attracts great concerns from the researchers. Based on the basic principles of IDA and the features of datasets that IDA handles, the development of IDA is briefly summarized from three aspects, i.e., algorithm principle, the scale and type of the dataset. Moreover, the challenges facing the IDA in big data environment are analyzed from four views, including big data management, data collection, data analysis, and application pattern. It is also cleared that in order to extract more values from data, the further development of IDA should combine practical applications and theoretical researches together.