A performance evaluation of preference evaluation techniques in real high dimensional database

Preference query has received high interest due to its great benefits over various types of database applications. This type of query provides more flexible query operator s that retrieve data items which are not dominated by the other data items in all attributes (dimensions). Many preference tech...

Full description

Saved in:
Bibliographic Details
Main Authors: Aljuboori, Ali A.Alwan, Ibrahim, Hamidah, Tan, Chik Yip, Udzir, Nur Izura, Sidi, Fatimah
Format: Article
Language:English
Published: Elsevier Ltd. 2012
Subjects:
Online Access:http://irep.iium.edu.my/36738/1/A_Perfromance_Evaluation_of_Preference_Evaluation_Techniques_in_Real_High_Dimenstional_Database.pdf
http://irep.iium.edu.my/36738/
http://www.sciencedirect.com/science/article/pii/S1877050912004759#
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Islam Antarabangsa Malaysia
Language: English
id my.iium.irep.36738
record_format dspace
spelling my.iium.irep.367382020-11-03T07:35:14Z http://irep.iium.edu.my/36738/ A performance evaluation of preference evaluation techniques in real high dimensional database Aljuboori, Ali A.Alwan Ibrahim, Hamidah Tan, Chik Yip Udzir, Nur Izura Sidi, Fatimah ZA4450 Databases Preference query has received high interest due to its great benefits over various types of database applications. This type of query provides more flexible query operator s that retrieve data items which are not dominated by the other data items in all attributes (dimensions). Many preference techniques for preference queries have been introduced including top-k, skyline, multi-objective skyline, top-k dominating, k-dominance, ranked skyline, and k-frequency. All of these preference techniques aimed at finding the “best” result that meets the user preferences. This paper aims at evaluating the performance of the five well-known preference evaluation techniques, namely: top-k , skyline, top-k dominating, k-dominance and k-frequency; in a real database application when high number of dimensions is the main concern. To achieve this, a recipe searching application with maximum number of 60 dimensions has been developed which assists users to identify the most desired recipes that fulfill their preferences. Several analyses have been carried out, where execution time is the main measurement used to evaluate each preference technique. Elsevier Ltd. 2012-08-27 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36738/1/A_Perfromance_Evaluation_of_Preference_Evaluation_Techniques_in_Real_High_Dimenstional_Database.pdf Aljuboori, Ali A.Alwan and Ibrahim, Hamidah and Tan, Chik Yip and Udzir, Nur Izura and Sidi, Fatimah (2012) A performance evaluation of preference evaluation techniques in real high dimensional database. Procedia Computer Science, 10. pp. 894-901. ISSN 1877-0509 http://www.sciencedirect.com/science/article/pii/S1877050912004759# 10.1016/j.procs.2012.06.118
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
Tan, Chik Yip
Udzir, Nur Izura
Sidi, Fatimah
A performance evaluation of preference evaluation techniques in real high dimensional database
description Preference query has received high interest due to its great benefits over various types of database applications. This type of query provides more flexible query operator s that retrieve data items which are not dominated by the other data items in all attributes (dimensions). Many preference techniques for preference queries have been introduced including top-k, skyline, multi-objective skyline, top-k dominating, k-dominance, ranked skyline, and k-frequency. All of these preference techniques aimed at finding the “best” result that meets the user preferences. This paper aims at evaluating the performance of the five well-known preference evaluation techniques, namely: top-k , skyline, top-k dominating, k-dominance and k-frequency; in a real database application when high number of dimensions is the main concern. To achieve this, a recipe searching application with maximum number of 60 dimensions has been developed which assists users to identify the most desired recipes that fulfill their preferences. Several analyses have been carried out, where execution time is the main measurement used to evaluate each preference technique.
format Article
author Aljuboori, Ali A.Alwan
Ibrahim, Hamidah
Tan, Chik Yip
Udzir, Nur Izura
Sidi, Fatimah
author_facet Aljuboori, Ali A.Alwan
Ibrahim, Hamidah
Tan, Chik Yip
Udzir, Nur Izura
Sidi, Fatimah
author_sort Aljuboori, Ali A.Alwan
title A performance evaluation of preference evaluation techniques in real high dimensional database
title_short A performance evaluation of preference evaluation techniques in real high dimensional database
title_full A performance evaluation of preference evaluation techniques in real high dimensional database
title_fullStr A performance evaluation of preference evaluation techniques in real high dimensional database
title_full_unstemmed A performance evaluation of preference evaluation techniques in real high dimensional database
title_sort performance evaluation of preference evaluation techniques in real high dimensional database
publisher Elsevier Ltd.
publishDate 2012
url http://irep.iium.edu.my/36738/1/A_Perfromance_Evaluation_of_Preference_Evaluation_Techniques_in_Real_High_Dimenstional_Database.pdf
http://irep.iium.edu.my/36738/
http://www.sciencedirect.com/science/article/pii/S1877050912004759#
_version_ 1683230332046802944