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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iium-369522018-06-19T07:57:09Z http://irep.iium.edu.my/36952/ A framework for evaluating skyline query over uncertain autonomous databases Mohd Saad, Nurul Husna Ibrahim, Hamidah Alwan, Ali Amer Sidi, Fatimah Yaakob, Razali QA75 Electronic computers. Computer science ZA4450 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, 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. Elsevier Ltd. 2014-06-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36952/1/A_Framework_for_Evaluating_Skyline_Query_over_Uncertain_Autonomous_Databases.pdf Mohd Saad, Nurul Husna and Ibrahim, Hamidah and Alwan, Ali Amer and Sidi, Fatimah and Yaakob, Razali (2014) A framework for evaluating skyline query over uncertain autonomous databases. Procedia Computer Science, 29. pp. 1546-1556. ISSN 1877-0509 http://www.sciencedirect.com/science/article/pii/S1877050914003172 10.1016/j.procs.2014.05.140 |
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topic |
QA75 Electronic computers. Computer science ZA4450 Databases |
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QA75 Electronic computers. Computer science ZA4450 Databases Mohd Saad, Nurul Husna Ibrahim, Hamidah Alwan, Ali Amer Sidi, Fatimah Yaakob, Razali A framework for evaluating skyline query over uncertain autonomous databases |
description |
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. |
format |
Article |
author |
Mohd Saad, Nurul Husna Ibrahim, Hamidah Alwan, Ali Amer Sidi, Fatimah Yaakob, Razali |
author_facet |
Mohd Saad, Nurul Husna Ibrahim, Hamidah Alwan, Ali Amer Sidi, Fatimah Yaakob, Razali |
author_sort |
Mohd Saad, Nurul Husna |
title |
A framework for evaluating skyline query over uncertain autonomous databases |
title_short |
A framework for evaluating skyline query over uncertain autonomous databases |
title_full |
A framework for evaluating skyline query over uncertain autonomous databases |
title_fullStr |
A framework for evaluating skyline query over uncertain autonomous databases |
title_full_unstemmed |
A framework for evaluating skyline query over uncertain autonomous databases |
title_sort |
framework for evaluating skyline query over uncertain autonomous databases |
publisher |
Elsevier Ltd. |
publishDate |
2014 |
url |
http://irep.iium.edu.my/36952/ http://irep.iium.edu.my/36952/ http://irep.iium.edu.my/36952/ http://irep.iium.edu.my/36952/1/A_Framework_for_Evaluating_Skyline_Query_over_Uncertain_Autonomous_Databases.pdf |
first_indexed |
2023-09-18T20:53:00Z |
last_indexed |
2023-09-18T20:53:00Z |
_version_ |
1777410119798095872 |