The top-k skyline groups query (k-SGQ) returns k skyline groups that dominate the maximum number of points in a given data set. It combines the advantages of skyline groups and top-k queries. The k-SGQ is an important tool for queries that need to analyze not only individual points but also groups of points, and can be widely used in areas such as decision support applications, market analysis ...

WELCOME to the fi rst issue of the IEEE Transactions on Services Computing in 2010. In this issue, I am pleased to publish six research papers, which include two regular submissions and four papers from a Special Section on Transactional Web Services. In this editorial preface, I would like to introduce these papers in the context of the body of knowledge areas of services computing. The theme ...

We propose an adaptive rendering approach for large-scale skyline characterization and matching with applications to automated geo-tagging of photos and images. Given an image, our system automatically extracts the skyline and then matches it to a database of reference skylines extracted from rendered images using digital elevation data (DEM). The sampling density of these rendering locations d...

Spatial skyline queries can be used in wireless sensor networks for collaborative positioning of multiple objects. However, designing a distributed spatial skyline algorithm in resource constrained wireless environments introduces several research challenges: how to distribute the computation of distances to multiple events in order to compute the skylines efficiently, accurately, quickly, prog...

solving a large sparse set of linear equations is of the problems widely seen in every numerical investigation in the entire range of engineering disciplines. employing a finite element approach in solving partial derivative equations, the resulting stiffness matrices would contain many zero-valued elements. moreover, storing all these sparse matrices in a computer memory would slower the compu...

Querying databases with preferences is an important research problem. Among various approaches to querying with preferences, the skyline framework is one of the most popular. A well known deficiency of that framework is that all attributes are of the same importance in skyline preference relations. Consequently, the size of the results of skyline queries may grow exponentially with the number o...

Skyline queries have recently received a lot of attention due to their intuitive query formulation: users can state preferences with respect to several attributes. Unlike numerical preferences, preferences over discrete value domains do not show an inherent total order, but have to rely on partial orders as stated by the user. In such orders typically many object values are incomparable, increa...

Skyline queries retrieve promising data objects that are not dominated in all the attributes of interest. However, in many cases, a user may not be interested in a skyline set computed over the entire dataset, but rather over a specified range of values for each attribute. For example, a user may look for hotels only within a specified budget and/or in a particular area in the city. This leads ...

This paper presents new results in external memory for finding the skyline (a.k.a. maxima) of N points in d-dimensional space. The state of the art uses O((N/B) log M/B(N/B)) I/Os for fixed d ≥ 3, and O((N/B) logM/B(N/B)) I/Os for d = 2, where M and B are the sizes (in words) of memory and a disk block, respectively. We give algorithms whose running time depends on the number K of points in the...