Abstract
Owing to the recent development of mobile computing and communication network technologies, efficiently retrieving relevant data from a huge spatial database has become more and more important. In this paper, we study a practical and novel problem of making recommendations by skyline query based on user locations and preferences. To achieve this goal, we address the multi-user location-dependent skyline query and introduce a new solution to solve it. By taking advantage of the dominance graph, we can reduce both the computational time cost and the memory occupation of our approach by dividing the query process into offline precomputation part and online computation part. The experiment results demonstrate that our algorithms significantly outperform the state-of-the-art methods.
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