期刊名称：International Journal of Database Management Systems
印刷版ISSN：0975-5985
电子版ISSN：0975-5705
出版年度：2015
卷号：7
期号：3
页码：1
DOI：10.5121/ijdms.2015.7301
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Several advanced applications require that uncertain data be stored in the database. Applications withsensor data, data mining, and integrated data are just few examples in which probabilistic data isconsidered a first class citizen. In response to this demand for storing and managing probabilistic data,researchers have started in recent years addressing issues pertaining to the management uncertain data.Representation and modeling of probabilistic data is one of the areas that needs attention. In this paper,we summarize our previous work on how probabilistic data can be represented along three differentprobability spaces, namely, attribute probability space, record probability space, and database stateprobability space. Then we introduce techniques for mapping the data from the attribute probability spaceto record probability space and from record probability space to database state probability space. Theability to perform correct mappings of data between these probability spaces is important in order topreserve the integrity of the data and avoid any data loss during the mapping process.
