Skyline queries computation on crowdsourced- enabled incomplete database
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 t...
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Online Access: | http://irep.iium.edu.my/80914/1/80914_Skyline%20Queries%20Computation.pdf http://irep.iium.edu.my/80914/7/80914_Skyline%20queries%20computation%20on%20crowdsourced_SCOPUS.pdf http://irep.iium.edu.my/80914/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9110574 |
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my.iium.irep.809142020-11-18T03:03:47Z http://irep.iium.edu.my/80914/ Skyline queries computation on crowdsourced- enabled incomplete database Swidan, Marwa Aljuboori, Ali A.Alwan Turaev, Sherzod Ibrahim, Hamidah Zaid Abualkishik, Abedallah Gulzar, Yonis QA75 Electronic computers. Computer science QA76 Computer software 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. IEEE 2020-06-18 Article PeerReviewed application/pdf en http://irep.iium.edu.my/80914/1/80914_Skyline%20Queries%20Computation.pdf application/pdf en http://irep.iium.edu.my/80914/7/80914_Skyline%20queries%20computation%20on%20crowdsourced_SCOPUS.pdf 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 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9110574 10.1109/ACCESS.2020.3000664 |
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QA75 Electronic computers. Computer science QA76 Computer software Swidan, Marwa Aljuboori, Ali A.Alwan Turaev, Sherzod Ibrahim, Hamidah Zaid Abualkishik, Abedallah Gulzar, Yonis Skyline queries computation on crowdsourced- enabled incomplete database |
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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. |
format |
Article |
author |
Swidan, Marwa Aljuboori, Ali A.Alwan Turaev, Sherzod Ibrahim, Hamidah Zaid Abualkishik, Abedallah Gulzar, Yonis |
author_facet |
Swidan, Marwa Aljuboori, Ali A.Alwan Turaev, Sherzod Ibrahim, Hamidah Zaid Abualkishik, Abedallah Gulzar, Yonis |
author_sort |
Swidan, Marwa |
title |
Skyline queries computation on crowdsourced-
enabled incomplete database |
title_short |
Skyline queries computation on crowdsourced-
enabled incomplete database |
title_full |
Skyline queries computation on crowdsourced-
enabled incomplete database |
title_fullStr |
Skyline queries computation on crowdsourced-
enabled incomplete database |
title_full_unstemmed |
Skyline queries computation on crowdsourced-
enabled incomplete database |
title_sort |
skyline queries computation on crowdsourced-
enabled incomplete database |
publisher |
IEEE |
publishDate |
2020 |
url |
http://irep.iium.edu.my/80914/1/80914_Skyline%20Queries%20Computation.pdf http://irep.iium.edu.my/80914/7/80914_Skyline%20queries%20computation%20on%20crowdsourced_SCOPUS.pdf http://irep.iium.edu.my/80914/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9110574 |
_version_ |
1684653058819096576 |
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13.18916 |