A Step forward for Spatial Skyline Queries for a Group of Users: Semantic in the Evidence Theory Setting.

Cities are the main poles of human and economic activity. Analyzing cities data is very important to improve the city economy as well as the life quality of the citizens. Since location based services and GPS devices can easily connect users located in different positions, it is worthwhile to optimize the efficiency of their shifting to a common location according to their preferences. For this reason, the support of advanced analysis queries such as the skyline operator has become important. This later finds the interesting objects according to a user preferences. However, data in such application can be uncertain, imprecise and incomplete. In this paper, we propose an imperfect spatial skyline query for users located in different positions. Detailed experimental analysis are reported. In addition, the theoretical properties developed in this paper help to devise efficient techniques to compute the spatial skyline over uncertain data fora set of users. Our extensive experiments show that the proposed algorithms provide quick initial response time.