Skyline queries may be used to filter interesting data from a broad range of data. A Skyline query selects those data that are the best according to multiple user-defined criteria. A special case of Skyline queries are the Spatial Skyline Queries (SSQ). SSQ allow users to express preferences on the closeness between a set of data points and a set of query points. We study the problem of answering SSQ in presence of changing data, i.e., data whose values regularly change over a period of time. In this chapter, it is proposed an algorithm to evaluate SSQ on changing data. The proposed algorithm is able to avoid recomputation of the whole Skyline with each update on the data. Also, the performance of the proposed algorithm against state-of-the-art algorithms was empirically studied. The experimental study shows that the proposed algorithm may become 3 times faster than state-of-the-art algorithms.
Spatial Skyline Queries: An Efficient Geometric Algorithm
