Given an integer k, a diverse skyline contains the k skyline points that best describe the tradeoffs (among different dimensions) offered by the full skyline. This paper gives an overview of the latest results on this topic. Specifically, we first describe the state-of-the-art formulation of diverse skylines. Then, we explain several algorithms for finding a diverse skyline, where the objective...

Admittedly, despite the plethora of scientometric indices proposed to rank scientists, none of them can fully capture the performance and impact of a scientist, since each index quantifies only one or a few aspects of his/her multifarious performance. Therefore, the task of scientometric ranking can be seen as a multi-dimensional ranking problem, where the different indices comprise the dimensi...

The skyline operator has been studied in database research for multi-criteria decision making. Until now the focus has been on the e ciency or accuracy of single queries. In practice, however, users are increasingly confronted with unknown data collections, where precise query formulation proves di cult. Instead, users explore the data in a sequence of incrementally changing queries to the data...

Skyline queries have emerged as an expressive and informative tool, with minimal user input and thus, they have gained widespread attention. However, previous research works tackle the problem from an efficiency standpoint, i.e., returning the skyline as fast as possible, leaving it to the user to manually inspect the entire skyline result. Clearly, this is impractical, even with a few dozen po...

Given a set of multi-dimensional points, a skyline query returns the interesting points that are not dominated by other points. It has been observed that the actual cardinality (s) of a skyline query result may differ substantially from the desired result cardinality (k), which has prompted studies on how to reduce s for the case where k < s. This paper goes further by addressing the general ca...

Skyline queries are useful in many applications such as multicriteria decision making, data mining, and user preference queries. A skyline query returns a set of interesting data objects that are not dominated in all dimensions by any other objects. For a high-dimensional database, sometimes it returns too many data objects to analyze intensively. To reduce the number of returned objects and to...

We propose a novel resilient drone service composition framework for delivery in dynamic weather conditions. use skyline approach to select an optimal set of candidate services at the source node skyway network. Drone are initially composed using constraint-aware deterministic lookahead algorithm multi-armed bandit tree exploration. heuristic-based that adapts runtime changes and periodically u...

People recently are interested in a new operator, called skyline [3], which returns the objects that are not dominated by any other objects with regard to certain measures in a multi-dimensional space. Recent work on the skyline operator [3, 15, 8, 13, 2] focuses on efficient computation of skylines in large databases. However, such work gives users only thin skylines, i.e., single objects, whi...

Skyline queries are useful for finding interesting tuples from a large data set according to multiple criteria. The sizes of data sets are constantly increasing and the architecture of back-ends are switching from single-node environments to non-conventional paradigms like MapReduce. Despite the usefulness of skyline queries, existing works on skyline computation in MapReduce do not take full a...

The task of similarity search in multimedia databases is usually accomplished by range or k nearest neighbor queries. However, the expressing power of these “single-example” queries fails when the user’s delicate query intent is not available as a single example. Recently, the well-known skyline operator was reused in metric similarity search as a “multi-example” query type. When applied on a m...