abstract saturated hydraulic conductivity (ks) is needed for many studies related to water and solute transport, but often cannot be measured because of practical and/or cost-related reasons. nonparametric approaches are being used in various fields to estimate continuous variables. one type of the nonparametric lazy learning algorithms, a k-nearest neighbor (k-nn) algorithm, was introduced and...

A k nearest neighbor (k-NN) query retrieves k objects in a given objects set which are closest to the query point q. Processing continuous k-nearest neighbor (k-NN) query over moving objects in location-dependent application requires that the frequent location updates of moving objects and intensive continuous k-NN queries must be efficiently processed at the same time. In this paper, we propos...

Text categorization refers to the task of assigning the pre-defined classes to text documents based on their content. k-NN algorithm is one of top performing classifiers on text data. However, there is little research work on the use of different voting methods over text data. Also, when a huge number of training data is available online, the response speed slows down, since a test document has...

This paper revisits the k-nearest-neighbor (k-NN) Voronoi diagram and presents the first output-sensitive paradigm for its construction. It introduces the k-NN Delaunay graph, which corresponds to the graph theoretic dual of the k-NN Voronoi diagram, and uses it as a base to directly compute the k-NN Voronoi diagram in R. In the L1, L∞ metrics this results in O((n + m) log n) time algorithm, us...