IIUM Repository

SCSA: Evaluating skyline queries in incomplete data

Gulzar, Yonis and Alwan, Ali Amer and Mohamed Abdullah, Radhwan and Xin, Qin and Swidan, Marwa (2019) SCSA: Evaluating skyline queries in incomplete data. Applied Intelligence Journal, 49 (5). pp. 1636-1657. ISSN 0924-669X E-ISSN 1573-7497 (In Press)

[img] PDF (Evidence from publisher's website for myra) - Published Version
Restricted to Repository staff only

Download (2MB) | Request a copy
[img]
Preview
PDF - Published Version
Download (236kB) | Preview
[img]
Preview
PDF (wos) - Supplemental Material
Download (299kB) | Preview

Abstract

Skyline queries have been extensively incorporated in various contemporary database applications. The list includes but is not limited to multi-criteria decision-making systems, decision support systems, and recommendation systems. Due to its great benefits and wide application range, many skyline algorithms have already been proposed in numerous data settings. Nonetheless, most researchers presume the completion of data meaning that all data item values are available. Since this assumption cannot be sustained in a large number of real-world database applications, the existing algorithms are rather inadequate to be directly applied on a database with incomplete data. In such cases, processing skyline queries on incomplete data incur exhaustive pairwise comparisons between data items, which may lead to loss of the transitivity property of the skyline technique. Losing the transitivity property may in turn give rise to the problem of cyclic dominance. In order to address these issues, we propose a new skyline algorithm called Sorting-based Cluster Skyline Algorithm (SCSA) that combines the sorting and partitioning techniques and simplifies the skyline computation on an incomplete dataset. These two techniques help boost the skyline process and avoid many unnecessary pairwise comparisons between data items to prune the dominated data items. The comprehensive experiments carried out on both synthetic and real-life datasets demonstrate the effectiveness and versatility of our approach as compared to the currently used approaches.

Item Type: Article (Journal)
Additional Information: 7094/68489
Uncontrolled Keywords: Skyline, Skyline queries, Incomplete data, Missing data, Preference queries, Query processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology

Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: DR. ALI A. ALWAN AL-JUBOORI
Date Deposited: 19 Dec 2018 09:22
Last Modified: 02 Jul 2020 16:58
URI: http://irep.iium.edu.my/id/eprint/68489

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year