Data uncertainty is ubiquitous in many real-world applications such as sensor/RFID data analysis. In this paper, we investigate uncertain data that exhibit local correlations, tha...
The class of k Nearest Neighbor (kNN) queries in spatial networks has been widely studied in the literature. All existing approaches for kNN search in spatial networks assume that ...
Ugur Demiryurek, Farnoush Banaei Kashani, Cyrus Sh...
—Subspaces offer convenient means of representing information in many pattern recognition, machine vision, and statistical learning applications. Contrary to the growing populari...
Efficiently processing continuous k-nearest neighbor queries on data streams is important in many application domains, e. g. for network intrusion detection or in querysubscriber ...
We propose a new data structure to compute the Delaunay triangulation of a set of points in the plane. It combines good worst case complexity, fast behavior on real data, small me...