The moving K diversified nearest neighbor query

Abstract

As a major type of continuous spatial queries, the moving k nearest neighbor (k NN) query has been studied extensively. However, most existing studies have focused on only the query efficiency. In this paper, we consider further the usability of the query results, in particular the diversification of the returned data points. We thereby formulate a new type of query named the moving k diversified nearest neighbor query (Mk DNN). This type of query continuously reports the k diversified nearest neighbors while the query object is moving. Here, the degree of diversity of the k NN set is defined on the distance between the objects in the k NN set. Computing the k diversified nearest neighbors i..