A framework for evaluating skyline query over uncertain autonomous databases
The perception of skyline query is to find a set of objects that is much preferred in all dimensions. While this theory is easily applicable on certain and complete database, however, when it comes to data integration of databases where each has different representation of data in a same dimension,...
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| 主要な著者: | , , , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
Elsevier
2014
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/31737/1/31737.pdf http://psasir.upm.edu.my/id/eprint/31737/ |
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| 要約: | The perception of skyline query is to find a set of objects that is much preferred in all dimensions. While this theory is easily applicable on certain and complete database, however, when it comes to data integration of databases where each has different representation of data in a same dimension, it would be difficult to determine the dominance relation between the underlying data. In this paper, we
propose a framework, SkyQUD, to efficiently compute the skyline probability of datasets in uncertain dimensions. We explore the effects of having datasets with uncertain dimensions in relation to the dominance relation theory and propose a framework that is able to support skyline queries on this type of datasets. |
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