Abstract
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.
Highlights
Prior to the first introduction of the skyline operator into database community by Borzsony et al (2001), there was a problem called maximum vector problem or Pareto optimum that has been addressed by (Bentley et al, 1978)
We presented and examined previous works related to processing skylines queries in incomplete databases
The focus is given on examining the strengths and the weaknesses of the solutions designed for skyline queries on incomplete database
Summary
Prior to the first introduction of the skyline operator into database community by Borzsony et al (2001), there was a problem called maximum vector problem or Pareto optimum that has been addressed by (Bentley et al, 1978). The incompleteness of data introduces new challenges in processing user queries on the databases and skyline queries, which involve the whole data items due to the process of pairwise comparison between the values of the database dimensions to identify the skylines. It has been reported that the missing values have a direct negative impact on processing skyline queries and in many cases, resulting high overhead, due to exhaustive pairwise comparisons between the data items.
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