Finding top k most influential spatial facilities over uncertain objects

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Conference Proceeding
ACM International Conference Proceeding Series, 2012, pp. 922 - 931
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Uncertainty is inherent in many important applications, such as location-based services (LBS), sensor monitoring and radio-frequency identification (RFID). Recently, considerable research efforts have been put into the field of uncertainty-aware spatial query processing. In this paper, we study the problem of finding top k most influential facilities over a set of uncertain objects, which is an important spatial query in the above applications. Based on the maximal utility principle, we propose a new ranking model to identify the top k most influential facilities, which carefully captures influence of facilities on the uncertain objects. By utilizing two uncertain object indexing techniques, R-tree and U-Quadtree, effective and efficient algorithms are proposed following the filtering and verification paradigm, which significantly improves the performance of the algorithms in terms of CPU and I/O costs. Comprehensive experiments on real datasets demonstrate the effectiveness and efficiency of our techniques. © 2012 ACM.
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