Processing skyline queries in incomplete distributed databases

Alwan, Ali A.; Ibrahim, Hamidah; Udzir, Nur Izura; Sidi, Fatimah

doi:10.1007/s10844-016-0419-2

Cited by 25 publications

(23 citation statements)

References 16 publications

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“…Several approaches have been proposed for handling missing information in skyline computation [21], [22], [23], [24], [25], [26], [27], [28], [37], [38]. This section presents previous approaches proposed to process skyline queries in the incomplete traditional database.…”

Section: A Skyline Queries For Incomplete Databasesmentioning

confidence: 99%

“…This phase tries to remove all the dominated tuples from the initial database in the early stage which has no contribution to form the final skylines results. To this end, a skyline algorithm is performed on the incomplete database that eliminates those dominated tuples [37]. The purpose of this process is to remove these dominated tuples with missing values from further processing.…”

Section: A Filtering Datamentioning

confidence: 99%

“…Moreover, two types of real datasets have been used which are NBA and Car databases. These real datasets are initially complete with no missing values; nevertheless, we have manipulated these datasets to be incomplete by randomly removing certain attribute values [4], [6], [20], [23], [27], [37]. The parameter setting of both the synthetic (correlated and independent) and real (NBA and Car) datasets have been described in Table 3.…”

Section: Experiments Evaluationmentioning

confidence: 99%

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Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

et al. 2020

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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.

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Section: A Skyline Queries For Incomplete Databasesmentioning

confidence: 99%

Section: A Filtering Datamentioning

confidence: 99%

Section: Experiments Evaluationmentioning

confidence: 99%

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Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

et al. 2020

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“…The work proposed in (Gulzar et al, 2019a) processes the skyline queries over cloud-based incomplete databases where data divided horizontally and stored in different data centers at different locations. Moreover, the work in (Alwan et al, 2017) proposed a skyline algorithm that intends to process skyline queries on incomplete distributed databases. They have proposed an algorithm named Jincoskyline that works on a vertically divided database stored in different relations.…”

Section: Skyline Queries In Crowd-sourced Databasesmentioning

confidence: 99%

An Overview of Query Processing on Crowdsourced Databases

Swidan¹,

Alwan²

2020

SJKFU

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Crowd-sourcing is a powerful solution to correctly answer expensive and unanswered queries in the database. This includes queries on a database with uncertain and incomplete data. The crowd-sourcing attempts to exploit human abilities to process these difficult tasks and workers helped to provide accurate results utilizing the available data in the crowd. The crowd-sourcing database systems (CSDB) combined the ability of the crowd with the relational database by using some variant of the relational database with minor changes. This paper surveys and examines the leading studies conducted on the area of query processing for both traditional and preference queries in crowd-sourcing databases. The focus is given on highlights the strengths and the weakness of each approach. A detailed discussion for the current and future trends research relevant to query processing in the area of crow-sourced databases is also demonstrated.

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“…The work contributed by Alwan et al (2017) focus on the issue of skyline query processing by proposing an approach for processing skyline queries in a distributed database with incomplete data. In their work, they assume that data is present in more than one relation and data is divided horizontally between relations.…”

Section: Related Literature Of Skyline Queries On Incomplete Databasesmentioning

confidence: 99%

Processing Skyline Queries in Incomplete Database: Issues, Challenges and Future Trends

Gulzar

Alwan

Salleh

et al. 2017

Journal of Computer Science

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In many contemporary database applications such as multi-criteria decision-making and real-time decision-support applications, data mining, ecommerce and recommendation systems, users need query operators to process the data aiming at finding the results that best fit with their preferences. Skyline queries are one of the most predominant query operators that privileges to find the query results that return only those data items whose dimension vector is not dominated by any other data item in the database. Because of their usefulness and ubiquity, skyline queries have been incorporated into different types of databases such as complete, incomplete and uncertain. This paper attempts to survey and analyze the previous works proposed to process skyline queries in the incomplete database. The discussion focuses on examining these approaches highlighting the strengths and the weaknesses of each work. Besides, we also discuss in detail the current challenges in processing skyline queries in the incomplete database and investigate the impact of incomplete data on skyline operation. A summary of the most well-known works has been reported to identify the limitations of these works. Some recommendations and future work directions have been drawn to help researchers investigate the unsolved problems related to skyline queries in a database system.

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Processing skyline queries in incomplete distributed databases

Cited by 25 publications

References 16 publications

Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

An Overview of Query Processing on Crowdsourced Databases

Processing Skyline Queries in Incomplete Database: Issues, Challenges and Future Trends

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