A survey on making skylines more flexible
Cem Cebeci
TL;DR
This survey reviews various methods for flexible skyline computation, addressing limitations of traditional top-k queries and skylines, and compares their properties to enhance multi-dimensional data analysis.
Contribution
It provides a comprehensive comparison of alternative approaches to traditional skyline and top-k queries, highlighting their strengths and weaknesses.
Findings
Alternative methods improve flexibility over traditional skylines.
Comparison clarifies which approaches meet specific scenario needs.
Highlights trade-offs in customization and output predictability.
Abstract
Top- queries and skylines are the two most common approaches to finding the most interesting entries in a homogeneous multi-dimensional dataset. However, both of these strategies have some shortcomings. Top- queries are very challenging to specify precisely and skylines are not customizable to specific scenarios, on top of having unpredictable output cardinalities. We describe some alternative methods aimed at addressing the shortcomings of top- queries and skylines and compare all approaches to illustrate which of the desired properties each of them possesses.
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Taxonomy
TopicsData Management and Algorithms · Automated Road and Building Extraction · Data Mining Algorithms and Applications