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Estimating missing values of skylines in incomplete database

Incompleteness of data is a common problem in many databases including web heterogeneous databases, multi-relational databases, spatial and temporal databases and data integration. The incompleteness of data introduces challenges in processing queries as providing accurate results that best meet the...

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Main Authors: Aljuboori, Ali A.Alwan, Ibrahim, Hamidah, Udzir, Nur Izura, Sidi, Fatimah
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
ZA4450 Databases
Online Access:http://irep.iium.edu.my/36673/1/b6b47ff5e3b0090f67f577d3533ee767%281%29.pdf
http://irep.iium.edu.my/36673/
http://sdiwc.net/digital-library/
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spelling my.iium.irep.366732020-11-03T07:30:01Z http://irep.iium.edu.my/36673/ Estimating missing values of skylines in incomplete database Aljuboori, Ali A.Alwan Ibrahim, Hamidah Udzir, Nur Izura Sidi, Fatimah ZA4450 Databases Incompleteness of data is a common problem in many databases including web heterogeneous databases, multi-relational databases, spatial and temporal databases and data integration. The incompleteness of data introduces challenges in processing queries as providing accurate results that best meet the query conditions over incomplete database is not a trivial task. Several techniques have been proposed to process queries in incomplete database. Some of these techniques retrieve the query results based on the existing values rather than estimating the missing values. Such techniques are undesirable in many cases as the dimensions with missing values might be the important dimensions of the user’s query. Besides, the output is incomplete and might not satisfy the user preferences. In this paper we propose an approach that estimates missing values in skylines to guide users in selecting the most appropriate skylines from the several candidate skylines. The approach utilizes the concept of mining attribute correlations to generate an Approximate Functional Dependencies (AFDs) that captured the relationships between the dimensions. Besides, identifying the strength of probability correlations to estimate the values. Then, the skylines with estimated values are ranked. By doing so, we ensure that the retrieved skylines are in the order of their estimated precision. 2013-03-04 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/36673/1/b6b47ff5e3b0090f67f577d3533ee767%281%29.pdf Aljuboori, Ali A.Alwan and Ibrahim, Hamidah and Udzir, Nur Izura and Sidi, Fatimah (2013) Estimating missing values of skylines in incomplete database. In: The Second International Conference on Digital Enterprise and Information Systems (DEIS 2013), 4th-6th March 2013, Kuala Lumpur. http://sdiwc.net/digital-library/
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic ZA4450 Databases
spellingShingle ZA4450 Databases
Aljuboori, Ali A.Alwan
Ibrahim, Hamidah
Udzir, Nur Izura
Sidi, Fatimah
Estimating missing values of skylines in incomplete database
description Incompleteness of data is a common problem in many databases including web heterogeneous databases, multi-relational databases, spatial and temporal databases and data integration. The incompleteness of data introduces challenges in processing queries as providing accurate results that best meet the query conditions over incomplete database is not a trivial task. Several techniques have been proposed to process queries in incomplete database. Some of these techniques retrieve the query results based on the existing values rather than estimating the missing values. Such techniques are undesirable in many cases as the dimensions with missing values might be the important dimensions of the user’s query. Besides, the output is incomplete and might not satisfy the user preferences. In this paper we propose an approach that estimates missing values in skylines to guide users in selecting the most appropriate skylines from the several candidate skylines. The approach utilizes the concept of mining attribute correlations to generate an Approximate Functional Dependencies (AFDs) that captured the relationships between the dimensions. Besides, identifying the strength of probability correlations to estimate the values. Then, the skylines with estimated values are ranked. By doing so, we ensure that the retrieved skylines are in the order of their estimated precision.
format Conference or Workshop Item
author Aljuboori, Ali A.Alwan
Ibrahim, Hamidah
Udzir, Nur Izura
Sidi, Fatimah
author_facet Aljuboori, Ali A.Alwan
Ibrahim, Hamidah
Udzir, Nur Izura
Sidi, Fatimah
author_sort Aljuboori, Ali A.Alwan
title Estimating missing values of skylines in incomplete database
title_short Estimating missing values of skylines in incomplete database
title_full Estimating missing values of skylines in incomplete database
title_fullStr Estimating missing values of skylines in incomplete database
title_full_unstemmed Estimating missing values of skylines in incomplete database
title_sort estimating missing values of skylines in incomplete database
publishDate 2013
url http://irep.iium.edu.my/36673/1/b6b47ff5e3b0090f67f577d3533ee767%281%29.pdf
http://irep.iium.edu.my/36673/
http://sdiwc.net/digital-library/
_version_ 1683230331906293760
score 13.211869

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