K-Nearest Neighbor Search for Moving Query Point

By Zhexuan Song, N. Roussopoulos. International Symposium on Spatial and Temporal Databases, 2001

385 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b3e9c0094d50be333e127f3e046829f0b37d6fe5

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In Computer Graphics and Computer-Aided Design

In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

Nearest Neighbor Search on Moving Object Trajectories (2005, methodology): “To our knowledge, in the literature such queries primarily deal with either static ([8], [2], [4]) or continuously moving query points ([11], [13]) over stationary datasets, or queries about the future positions of a set of continuously moving points ([1], [12], [5]).”
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring (2005, background): “Song and Roussopoulos [SR01] reduce the number of moving NN queries over static objects by introducing some redundancy.”
Location-based spatial queries (2003, methodology): “The first spatial query processing techniques for mobile computing were proposed in [ZL01] and [SR01], both dealing with moving nearest neighbor queries on static data.”
Querying imprecise data in moving object environments (2003, background): “Song and Roussopoulos [20] investigate how to execute k-nearest neighbor queries for moving query point efficiently.”
SINA: scalable incremental processing of continuous queries in spatio-temporal databases (2004, methodology): “, see [2, 23, 25, 32]), scalability, incremental evaluation, mutability of both objects and queries, and client overhead are examples of challenges that either are overlooked wholly or partially by previous approaches.”
Continuous Nearest Neighbor Search (2002, methodology): “The first algorithm for CNN query processing, proposed in [SR01], employs sampling to compute the result.”
Nearest neighbor and reverse nearest neighbor queries for moving objects (2002, background): “While much work has been conducted on algorithms for nearest neighbor queries, we are aware of only one work that has explored algorithms for a moving query point and static data points [22] and of no solutions for moving data and query points in two or higher dimensional space.”
SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases (2005, methodology): “[28] and [29] are restricted to the case of moving queries over stationary objects.”