Monitoring Aggregate k-NN Objects in Road Networks
نویسندگان
چکیده
In recent years, there is an increasing need to monitor k nearest neighbor (k-NN) in a road network. There are existing solutions on either monitoring k-NN objects from a single query point over a road network, or computing the snapshot k-NN objects over a road network to minimize an aggregate distance function with respect to multiple query points. In this paper, we study a new problem that is to monitor k-NN objects over a road network from multiple query points to minimize an aggregate distance function with respect to the multiple query points. We call it a continuous aggregate k-NN (CANN) query. We propose a new approach that can significantly reduce the cost of computing network distances when monitoring aggregate k-NN objects on road networks. We conducted extensive experimental studies and confirmed the efficiency of our algorithms.
منابع مشابه
Kyriakos MOURATIDIS School of Information Systems
Continuous Nearest Neighbor Monitoring A k nearest neighbor (k-NN) query retrieves the k objects in a dataset that lie closest to a given query point. There exist numerous approaches for efficient k-NN processing over static datasets. Recently, however, the research focus has shifted towards dynamic environments where (i) the data objects and the query points move in an unpredictable manner, an...
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