Monitoring the top-m rank aggregation of spatial objects in streaming queries

Abstract

In this paper, we propose and study the problem of top-m rank aggregation of spatial objects in streaming queries, where, given a set of objects O, a stream of spatial queries (kNN or range), the goal is to report the m objects with the highest aggregate rank. The rank of an object with respect to an individual query is computed based on its distance from the query location, and the aggregate rank is computed from all of the individual rank orderings. In order to solve this problem, we show how to upper and lower bound the rank of an object for any unseen query. Then we propose an approximation solution to continuously monitor the top-m objects efficiently, for which we design an Inverted Ra..