Answering range-based reverse kNN and why-not reverse kNN queries

Given a dataset D and a point q, a reverse nearest neighbor (RNN) query retrieves all the points p ∈ D that have q as their nearest neighbor. Although the RNN problem was first proposed in [1], it still has received considerable attention due to its importance in several applications involving decision support, resource allocation, profile-based marketing, etc. Despite significant progress on this problem, there is a research gap in finding RNNs not just for an object, but for a given range, which is a natural extension of the problem. In this paper, we proposed a range-based reverse k nearest neighbors (RRkNN) query, it retrieves all the points p ∈ D that have any position in the query range R as their kNN. It is useful in our daily life. In this paper, We assume that the shape of range R is rectangle. Moreover, in the last several decades, the database systems have been greatly developed. As explained applications become more practical, these systems should be more userfriendly, interactive and cooperative. That is, users are not satisfied with only receiving the query answer, but also want to know why the system returns the current set. If the database system can offer a good explanation for the query answer set, it would be very helpful for users to understand the information needed and thus refine her initial query [2, 3]. For example, taxi-hailing applications are very popular nowadays. When a cab driver using a taxi-hailing app, he wants to