Identifying the queried object, from a large volume of given uncertain dataset, is a tedious
task which involves time complexity and computational complexity. To solve these …

With the continued proliferation of wireless communications and advances in positioning
technologies, algorithms for efficiently answering queries about large populations of moving …

Given a point q, a reverse k nearest neighbor (RkNN) query retrieves all the data points that
have q as one of their k nearest neighbors. Existing methods for processing such queries …

Reverse Nearest Neighbor (RNN) queries are of particular interest in a wide range of
applications such as decision support systems, profile based marketing, data streaming …

Given a set O of weighted objects, a set S of sites, and a query site s, the bichromatic RNN
query computes the influence set of s, or the set of objects in O that consider s as the nearest …

Given a set\cal D of objects, a reverse nearest neighbor (RNN) query returns the objects o
in\cal D such that o is closer to a query object q than to any other object in\cal D, according …

Continuous spatio-temporal queries have recently received increasing attention due to the
abundance of location-aware applications. This paper addresses the Continuous Reverse …

Given a multidimensional point q, a reverse k nearest neighbor (R k NN) query retrieves all
the data points that have q as one of their k nearest neighbors. Existing methods for …

In the typical nonparametric approach to classification in instance-based learning and data
mining, random data (the training set of patterns) are collected and used to design a …

For a finite set of points S, the (monochromatic) reverse nearest neighbor (RNN) rule
associates with any query point q the subset of points in S that have q as its nearest …