IIUM Repository

Skyline queries computation on crowdsourced- enabled incomplete database

Swidan, Marwa and Aljuboori, Ali A.Alwan and Turaev, Sherzod and Ibrahim, Hamidah and Zaid Abualkishik, Abedallah and Gulzar, Yonis (2020) Skyline queries computation on crowdsourced- enabled incomplete database. IEEE Access, 8. pp. 106660-106689. E-ISSN 2169-3536

[img]
Preview
PDF - Published Version
Download (3MB) | Preview

Abstract

Data incompleteness becomes a frequent phenomenon in a large number of contemporary database applications such as web autonomous databases, big data, and crowd-sourced databases. Processing skyline queries over incomplete databases impose a number of challenges that negatively influence processing the skyline queries. Most importantly, the skylines derived from incomplete databases are also incomplete in which some values are missing. Retrieving skylines with missing values is undesirable, particularly, for recommendation and decision-making systems. Furthermore, running skyline queries on a database with incomplete data raises a number of issues influence processing skyline queries such as losing the transitivity property of the skyline technique and cyclic dominance between the tuples. The issue of estimating the missing values of skylines has been discussed and examined in the database literature. Most recently, several studies have suggested exploiting the crowd-sourced databases in order to estimate the missing values by generating plausible values using the crowd. Crowd-sourced databases have proved to be a powerful solution to perform user-given tasks by integrating human intelligence and experience to process the tasks. However, task processing using crowd-sourced incurs additional monetary cost and increases the time latency. Also, it is not always possible to produce a satisfactory result that meets the user's preferences. This paper proposes an approach for estimating the missing values of the skylines by first exploiting the available data and utilizes the implicit relationships between the attributes in order to impute the missing values of the skylines. This process aims at reducing the number of values to be estimated using the crowd when local estimation is inappropriate. Intensive experiments on both synthetic and real datasets have been accomplished. The experimental results have proven that the proposed approach for estimating the missing values of the skylines over crowd-sourced enabled incomplete databases is scalable and outperforms the other existing approaches.

Item Type: Article (Journal)
Additional Information: 7094/80914
Uncontrolled Keywords: Incomplete data, crowdsourcing databases, approximate functional dependencies, query processing, skylines, skyline queries
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 > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science

Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology
Depositing User: DR. ALI A. ALWAN AL-JUBOORI
Date Deposited: 24 Jun 2020 11:32
Last Modified: 24 Jun 2020 11:32
URI: http://irep.iium.edu.my/id/eprint/80914

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year