Skyline queries return a set of objects, or a skyline, that are not dominated by any other objects. While providing users with an intuitive query formulation, the skyline queries may incur too many results, especially, for high dimensional data. To tackle this problem, subspace skyline queries, which deals with a subset of dimensions, have been recently studied. To identify interesting skylines, users can iteratively refine multiple relevant subspaces for skyline queries. Existing work focuses primarily on supporting efficient subspace skyline computation in centralized databases. In clear contrast, this paper aims to address subspace skyline computation in distributed environments such as the Web. Toward this goal, we make use of pre-compu...
Skyline queries are useful in many applications such as multi-criteria decision making, data mining,...
Skyline queries help users make intelligent decisions over complex data, where different and often c...
Skyline queries are capable of retrieving interesting points from a large data set according to mult...
Abstract. Skyline queries have gained much attention as alternative query semantics with pros (e.g.l...
Skyline has been proposed as an important operator for many applications, such as multi-criteria dec...
Skyline queries have attracted considerable attention to assist multicriteria analysis of large-scal...
Given a set of k-dimensional objects, the skyline query finds the objects that are not dominated by ...
Skyline query processing has received considerable at-tention in the recent past. Mainly, the skylin...
Skyline queries return a set of interesting data points that are not dominated on all dimensions by ...
The skyline operator of a $d$-dimensional dataset, which returns the points that are not dominated b...
Given a set of multidimensional data points, skyline queries retrieve those points that are not domi...
The skyline operator returns from a set of multi-dimensional objects a subset of superior objects th...
Skyline computation is important in applications that involve multi-criteria decision making. In thi...
The skyline of a multidimensional point set is a subset of interesting points that are not dominated...
Given a set of multi-dimensional points, the skyline contains the best points according to any prefe...
Skyline queries are useful in many applications such as multi-criteria decision making, data mining,...
Skyline queries help users make intelligent decisions over complex data, where different and often c...
Skyline queries are capable of retrieving interesting points from a large data set according to mult...
Abstract. Skyline queries have gained much attention as alternative query semantics with pros (e.g.l...
Skyline has been proposed as an important operator for many applications, such as multi-criteria dec...
Skyline queries have attracted considerable attention to assist multicriteria analysis of large-scal...
Given a set of k-dimensional objects, the skyline query finds the objects that are not dominated by ...
Skyline query processing has received considerable at-tention in the recent past. Mainly, the skylin...
Skyline queries return a set of interesting data points that are not dominated on all dimensions by ...
The skyline operator of a $d$-dimensional dataset, which returns the points that are not dominated b...
Given a set of multidimensional data points, skyline queries retrieve those points that are not domi...
The skyline operator returns from a set of multi-dimensional objects a subset of superior objects th...
Skyline computation is important in applications that involve multi-criteria decision making. In thi...
The skyline of a multidimensional point set is a subset of interesting points that are not dominated...
Given a set of multi-dimensional points, the skyline contains the best points according to any prefe...
Skyline queries are useful in many applications such as multi-criteria decision making, data mining,...
Skyline queries help users make intelligent decisions over complex data, where different and often c...
Skyline queries are capable of retrieving interesting points from a large data set according to mult...