Skyline Preference Query Based on Massive and Incomplete Dataset

Wang, Yan; Shi, Zhan; Wang, Junlu; Sun, Li; Song, Baoyan

doi:10.1109/access.2016.2639558

Cited by 24 publications

(22 citation statements)

References 12 publications

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“…The novel skyline preference query strategy is based on a massive and incomplete data set proposed by [29]. This strategy is named SPQ algorithm that divides massive and incomplete data set into two parts according to attribute importance and executes a skyline query.…”

Section: A Skyline Queries For Incomplete Databasesmentioning

confidence: 99%

“…It is suggested that the process of generating precise value estimation on a large volume database with a high missing rate constitutes an exhaustive and time-consuming process [20], [23], [26], [29], [31], [33], [41]. This is due to the fact that the process of estimating the missing database values requires the scanning and examining of all the available data in order to capture the implicit relationships between the attributes that help produce a precise estimated value.…”

Section: Effect Of Data Filtrationmentioning

confidence: 99%

“…To solve the above problem of skyline computation over incomplete data, many approaches of skyline query processing on the traditional incomplete database have been proposed. This includes Iskyline [20], RBSSQ [25], Sortbased Incomplete Data Skyline (SIDS) [26], Incomplete Data Frequent Skyline (IDFS) [27], KISB and VP [28], IncoSkyline [21], IDS and SPQ [29], ISSA [30] and SCSA [22]. These approaches have introduced solutions to the issue of processing skyline queries on incomplete databases without paying attention to manipulating the missing values of the skylines.…”

Section: Introductionmentioning

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: Effect Of Data Filtrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

et al. 2020

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“…x and ||•|| l is the normalized Frobenius norm. (30) On the basis of information entropy theory, (31) the greater fluctuation in ,…”

Section: B I Jmentioning

confidence: 99%

A Machine-learning-enabled Context-driven Control Mechanism for Software-defined Smart Home Networks

Ru¹,

Chu²,

Zhang³

et al. 2019

Sensors and Materials

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“…Lastly, the global skylines are determined by carrying out the domination test between data item. Wang et al (2017) have also highlighted the issue of processing skyline queries over massive incomplete data. They proposed an approach named Skyline Preference Query (SPQ) which operate on a large volume of a database with incomplete data.…”

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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Skyline Preference Query Based on Massive and Incomplete Dataset

Cited by 24 publications

References 12 publications

Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

Skyline Queries Computation on Crowdsourced- Enabled Incomplete Database

A Machine-learning-enabled Context-driven Control Mechanism for Software-defined Smart Home Networks

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

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