Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data


Choenni, Sunil and Blok, Henk Ernst and Leertouwer, Erik (2006) Handling Uncertainty and Ignorance in Databases: A Rule to Combine Dependent Data. In: 11th International Conference on Database Systems for Advanced Applications, DASFAA 2006, April 12-15, 2006, Singapore (pp. pp. 310-324).

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Abstract:In many applications, uncertainty and ignorance go hand in hand. Therefore, to deliver database support for effective decision making, an integrated view of uncertainty and ignorance should be taken. So far, most of the efforts attempted to capture uncertainty and ignorance with probability theory. In this paper, we discuss the weakness to capture ignorance with probability theory, and propose an approach inspired by the Dempster-Shafer theory to capture uncertainty and ignorance. Then, we present a rule to combine dependent data that are represented in different relations. Such a rule is required to perform joins in a consistent way. We illustrate that our rule is able to solve the so-called problem of information loss, which was considered as an open problem so far.
Item Type:Conference or Workshop Item
Copyright:© 2006 Springer
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/63575
Official URL:https://doi.org/10.1007/11733836_23
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