Skyline-Like Query in Three-Dimensional Obstacle Space

Abstract

Skyline query, as a query method to solve typical multiobjective optimization problems, has a wide range of applications in market analysis and data mining. Many scholars’ attention has been attracted since it was proposed. However, the correct result set cannot be obtained easily by traditional skyline query when nonspatial and spatial attributes of the data set need to be considered at the same time, and there are differences in the importance of each attribute. To solve this problem, a skyline-like query was proposed in three-dimensional obstacle space based on the traditional skyline query. In the skyline-like query algorithm, nonspatial skyline-like points were obtained according to the traditional algorithm. The spatial attribute dominated region of the obtained points was used to filter the data set, and then the shielding of obstacles was considered in the three-dimensional obstacle space. By constructing a three-dimensional visible graph, the Dijkstra algorithm was used to obtain the skyline-like points of spatial attribute. After sorting, the skyline-like point set was obtained based on the value of user’s preference. Compared with B2S2 algorithm, the experimental results show that the skyline-like algorithm had a better performance. Then, the comparative experiments within three-dimensional obstacle skyline query were carried out by setting different sizes of data sets and different numbers of obstacles. According to the results, it is shown that the algorithm had a great performance.