{"title":"上下文感知系统中不确定性的建模和推理","authors":"Binh An Truong, Young-Koo Lee, Sungyoung Lee","doi":"10.1109/ICEBE.2005.90","DOIUrl":null,"url":null,"abstract":"Uncertainty always exists as an unavoidable factor when developing context-aware applications for pervasive computing environments. In this paper, we propose a unified context model to support representation and reasoning about uncertain context. Our unified context model extends the existing, de-facto ontology-based context models with probabilistic models to support probabilistic reasoning. Especially, our context model can be easily integrated with existing ontology-based context-aware systems. Given the unified context model, unified context ontology can be built and used as frameworks in developing context aware applications. Besides, our recipe of supporting the probabilistic reasoning is flexible and adaptive to the highly variable features of pervasive computing environments","PeriodicalId":118472,"journal":{"name":"IEEE International Conference on e-Business Engineering (ICEBE'05)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":"{\"title\":\"Modeling and reasoning about uncertainty in context-aware systems\",\"authors\":\"Binh An Truong, Young-Koo Lee, Sungyoung Lee\",\"doi\":\"10.1109/ICEBE.2005.90\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Uncertainty always exists as an unavoidable factor when developing context-aware applications for pervasive computing environments. In this paper, we propose a unified context model to support representation and reasoning about uncertain context. Our unified context model extends the existing, de-facto ontology-based context models with probabilistic models to support probabilistic reasoning. Especially, our context model can be easily integrated with existing ontology-based context-aware systems. Given the unified context model, unified context ontology can be built and used as frameworks in developing context aware applications. Besides, our recipe of supporting the probabilistic reasoning is flexible and adaptive to the highly variable features of pervasive computing environments\",\"PeriodicalId\":118472,\"journal\":{\"name\":\"IEEE International Conference on e-Business Engineering (ICEBE'05)\",\"volume\":\"180 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"45\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on e-Business Engineering (ICEBE'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEBE.2005.90\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on e-Business Engineering (ICEBE'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEBE.2005.90","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and reasoning about uncertainty in context-aware systems
Uncertainty always exists as an unavoidable factor when developing context-aware applications for pervasive computing environments. In this paper, we propose a unified context model to support representation and reasoning about uncertain context. Our unified context model extends the existing, de-facto ontology-based context models with probabilistic models to support probabilistic reasoning. Especially, our context model can be easily integrated with existing ontology-based context-aware systems. Given the unified context model, unified context ontology can be built and used as frameworks in developing context aware applications. Besides, our recipe of supporting the probabilistic reasoning is flexible and adaptive to the highly variable features of pervasive computing environments