Utilizing spatial index structures on secondary memory for nearest neighbor search in high-dimensional data spaces has been the subject of much research. With the potential to host...
Christoph Brochhaus, Marc Wichterich, Thomas Seidl
Abstract. We propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem in Euclidean spaces. Compared to the limitations of existing methods for ...
The tremendous growth of the Internet has significantly reduced the cost of obtaining and sharing information about individuals, raising many concerns about user privacy. Spatial...
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Complex networks, such as biological, social, and communication networks, often entail uncertainty, and thus, can be modeled as probabilistic graphs. Similar to the problem of sim...
Michalis Potamias, Francesco Bonchi, Aristides Gio...