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...

Full description

Bibliographic Details
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/ http://irep.iium.edu.my/36673/ http://irep.iium.edu.my/36673/1/b6b47ff5e3b0090f67f577d3533ee767%281%29.pdf

id	iium-36673
recordtype	eprints
spelling	iium-366732014-05-28T07:45:41Z 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/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
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/ http://irep.iium.edu.my/36673/ http://irep.iium.edu.my/36673/1/b6b47ff5e3b0090f67f577d3533ee767%281%29.pdf
first_indexed	2023-09-18T20:52:33Z
last_indexed	2023-09-18T20:52:33Z
_version_	1777410090517659648

Estimating missing values of skylines in incomplete database

Similar Items