Related papers: Spatial Skyline Queries: An Efficient Geometric Al…
The techniques most extensively used to retrieve interesting data from data-sets are the Skyline and the Top-k queries. Sadly, they are not enough for facing modern problems, so the needing of something more usable and reliable has come. In…
The question of how to get the best results out of the data we have is an everlasting problem in data science. The two main approaches to tackle the problem are top-k queries and skyline queries. Since their introduction, a new paradigm…
Skyline, aiming at finding a Pareto optimal subset of points in a multi-dimensional dataset, has gained great interest due to its extensive use for multi-criteria analysis and decision making. The skyline consists of all points that are not…
With the advancement of technology, the data generated in our lives is getting faster and faster, and the amount of data that various applications need to process becomes extremely huge. Therefore, we need to put more effort into analyzing…
The Wireless GIS technology is progressing rapidly in the area of mobile communications. Location-based spatial queries are becoming an integral part of many new mobile applications. The Skyline queries are latest apps under Location-based…
Top-$k$ 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-$k$ queries are very…
Nowadays, as the quantity of data to process began to rise, so did the need for a method to discern what pieces of information could be useful for the user; in response, researchers focused their efforts on improving the already existing…
Skyline computation aims at looking for the set of tuples that are not worse than any other tuples in all dimensions from a multidimensional database. In this paper, we present SDI (Skyline on Dimension Index), a dimension indexing…
Given a set of multidimensional points, the skyline operator returns a set of potentially interesting points from such a dataset. This popular operator filters out a set of tuples that are not dominated by other ones, reducing the size of a…
Given a set of $n$ points in a $d$-dimensional space, we seek to compute the skyline, i.e., those points that are not strictly dominated by any other point, using few comparisons between elements. We adopt the noisy comparison model…
To retrieve the best results in a database we use Top-K queries and Skyline queries but some problems arise. The formers rely too much on user preferences, which are difficult to quantify and may skew the fetching of the data, while the…
A set of preferred records can be obtained from a large database in a multi-criteria setting using various computational methods which either depend on the concept of dominance or on the concept of utility or scoring function based on the…
Nowadays, efficient and effective processing over massive stream data has attracted much attention from the database community, which are useful in many real applications such as sensor data monitoring, network intrusion detection, and so…
The computation of the skyline provides a mechanism for utilizing multiple location-based criteria to identify optimal data points. However, the efficiency of these computations diminishes and becomes more challenging as the input data…
Strong Lensing is a powerful probe of the matter distribution in galaxies and clusters and a relevant tool for cosmography. Analyses of strong gravitational lenses with Deep Learning have become a popular approach due to these astronomical…
Recent studies pointed out some limitations about classic top-k queries and skyline queries. Ranking queries impose the user to provide a specific scoring function, which can lead to the exclusion of interesting results because of the…
While classical skyline queries identify interesting data within large datasets, flexible skylines introduce preferences through constraints on attribute weights, and further reduce the data returned. However, computing these queries can be…
This paper presents a new application for multi-dimensional Skyline query. The idea presented in this paper can be used to find best shopping malls based on users requirements. A web-based application was used to simulate the problem and…
Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented reality applications. We present a novel mountainous skyline detection approach where we adapt a…
The most common archetypes to identify relevant information in large datasets and find the bestoptions according to some preferences or user criteria, are the top-k queries (ranking method based ona score function defined over the records…