{"title":"Context Based Data Verifying Method in Ubiquitous Computing Environment","authors":"Keonsoo Lee, Seungmin Rho, Minkoo Kim","doi":"10.1109/ITCS.2010.5581276","DOIUrl":null,"url":null,"abstract":"The ability of recognizing the environment is one of the most important functions that the ubiquitous computing system should have. With the recognition of the environment, the system can execute intelligent behaviors such as runtime configuration and semantic based process branch. This recognition can be used as context for system???s decision making. And with correct context, the system can make a proper decision. In this paper, data verifying method is proposed. This method validates the sensed data for the environment. From the proved data, the more reliable recognition of the environment can be generated. The proposed method employs probability theory for marking the reliable degree and machine learning for interpreting the semantic meaning of validated data.","PeriodicalId":166169,"journal":{"name":"2010 2nd International Conference on Information Technology Convergence and Services","volume":"82 17","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Conference on Information Technology Convergence and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITCS.2010.5581276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The ability of recognizing the environment is one of the most important functions that the ubiquitous computing system should have. With the recognition of the environment, the system can execute intelligent behaviors such as runtime configuration and semantic based process branch. This recognition can be used as context for system???s decision making. And with correct context, the system can make a proper decision. In this paper, data verifying method is proposed. This method validates the sensed data for the environment. From the proved data, the more reliable recognition of the environment can be generated. The proposed method employs probability theory for marking the reliable degree and machine learning for interpreting the semantic meaning of validated data.