Processing Incomplete <italic>k</italic> Nearest Neighbor Search
نویسندگان
چکیده
منابع مشابه
Continuous Nearest Neighbor Search
A continuous nearest neighbor query retrieves the nearest neighbor (NN) of every point on a line segment (e.g., “find all my nearest gas stations during my route from point s to point e”). The result contains a set of tuples, such that point is the NN of all points in the corresponding interval. Existing methods for continuous nearest neighbor search are based on the repetitiv...
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A fundamental activity common to image processing, pattern recognition, and clustering algorithm involves searching set of n , k-dimensional data for one which is nearest to a given target data with respect to distance function . Our goal is to find search algorithms with are full search equivalent -which is resulting match as a good as we could obtain if we were to search the set exhausting. 1...
متن کاملNearest neighbor search
Definition 1.1. Nearest Neighbor Search: Given a set of points {x1, . . . , xn} ∈ R preprocess them into a data structure X of size poly(n, d) in time poly(n, d) such that nearest neighbor queries can be performed in logarithmic time. In other words, given a search point q a radius r and X one can return an xi such the ||q − xi|| ≤ r or nothing if no such point exists. The search for xi should ...
متن کاملSimultaneous Nearest Neighbor Search
Motivated by applications in computer vision and databases, we introduce and study the Simultaneous Nearest Neighbor Search (SNN) problem. Given a set of data points, the goal of SNN is to design a data structure that, given a collection of queries, finds a collection of close points that are “compatible” with each other. Formally, we are given k query points Q = q1, · · · , qk, and a compatibi...
متن کاملFast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph
We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.
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ژورنال
عنوان ژورنال: IEEE Transactions on Fuzzy Systems
سال: 2016
ISSN: 1063-6706,1941-0034
DOI: 10.1109/tfuzz.2016.2516562