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An efficient k nearest neighbors searching algorithm for a query line
2003
Theoretical Computer Science
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We present an algorithm for ÿnding k nearest neighbors of a given query line among a set of n points distributed arbitrarily on a two-dimensional plane. ...
Our algorithm requires O(n 2 ) time and O(n 2 =log n) space to preprocess the given set of points, and it answers the query for a given line in O(k + log n) time, where k may also be an input at the query ...
Harayama for helpful discussions. The critical comments and suggestions given by the referees helped the authors to improve the presentation of the paper. ...
doi:10.1016/s0304-3975(02)00322-5
fatcat:kamdg5o4ibgovjrbdzlvsm2s2i
Efficient k-nearest neighbor searches for multi-source forest attribute mapping
2008
Remote Sensing of Environment
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In this study, we explore the utility of data structures that facilitate efficient nearest neighbor searches for application in multi-source forest attribute prediction. ...
Further, given our trial data, we found that enormous gain in search time efficiency, afforded by approximate nearest neighbor search algorithms, does not result in compromised kNN prediction. ...
One disadvantage of the method, limiting its utility, is the computationally intensive search for the nearest neighbor subset. For a small number of queries, search time is not an issue. ...
doi:10.1016/j.rse.2007.08.024
fatcat:llgrkpcizfha5j6u42mct76tem
Survey of Nearest Neighbor Techniques
[article]
2010
arXiv
pre-print
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Weighted kNN, Model based kNN, Condensed NN, Reduced NN, Generalized NN are structure less techniques whereas k-d tree, ball tree, Principal Axis Tree, Nearest Feature Line, Tunable NN, Orthogonal Search ...
The nearest neighbor (NN) technique is very simple, highly efficient and effective in the field of pattern recognition, text categorization, object recognition etc. ...
Center based Nearest Neighbor (CNN) [27] A Center Line is calculated 1.Highly efficient for small data sets 1. ...
arXiv:1007.0085v1
fatcat:uwac2xtmhnajvoxjrhjnsf3xwy
The ANN-tree: an index for efficient approximate nearest neighbor search
2001
Proceedings Seventh International Conference on Database Systems for Advanced Applications DASFAA 2001 DASFAA-01
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This m a k e s the A N N -t r e e a preferable i n d e x structure f o r both exact and approximate nearest neighbor searches. ...
E v e n if a n exact nearest nearest neighbor query is desired, t h e A N N -t r e e i s demonstrably m o r e efficient t h a n existing structures like t h e R *-tree. ...
QED The above theorem provides a sufficient condition for an index to have a correct minimum access nearest neighbor search algorithm. ...
doi:10.1109/dasfaa.2001.916376
dblp:conf/dasfaa/LinY01
fatcat:7bnurof2trbpjl6xrfwzgk43u4
A Simple Framework for the Generalized Nearest Neighbor Problem
[chapter]
2012
Lecture Notes in Computer Science
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The problem of finding a nearest neighbor from a set of points in R d to a complex query object has attracted considerable attention due to various applications in computational geometry, bio-informatics ...
We propose a generic method that solves the problem for various classes of query objects and distance functions in a unified way. ...
We are also grateful to Jiri Matoušek for several discussions on the duality, arrangements and tricky details. ...
doi:10.1007/978-3-642-31155-0_8
fatcat:ejknzg4z7jcc3ekeimlu6g24te
Continuous All k-Nearest-Neighbor Querying in Smartphone Networks
2012
2012 IEEE 13th International Conference on Mobile Data Management
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Consider a centralized query operator that identifies to every smartphone user its k geographically nearest neighbors at all times, a query we coin Continuous All k-Nearest Neighbor (CAkNN). ...
We introduce an algorithm, coined Proximity, which answers CAkNN queries in O(n(k + λ)) time, where n denotes the number of users and λ a network-specific parameter (λ << n). ...
Manolis Spanakis for the help with the Manhattan dataset. ...
doi:10.1109/mdm.2012.19
dblp:conf/mdm/ChatzimilioudisZLD12
fatcat:odzj4o4zznh5bh3yr6nxfkrime
kANN on the GPU with Shifted Sorting
[article]
2012
High Performance Graphics
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We describe the implementation of a simple method for finding k approximate nearest neighbors (ANNs) on the GPU. ...
Irrespective of the distribution and also roughly of the size of the set of input data points, we can find 50 ANNs for 1M queries at a rate of about 1200 queries/ms. ...
We would also like to thank Andrew Davidson and Anjul Patney for their ideas and insight. ...
doi:10.2312/eggh/hpg12/039-047
fatcat:mo263xa6z5f2hbejx7u62egjve
Optimal multi-step k-nearest neighbor search
1998
Proceedings of the 1998 ACM SIGMOD international conference on Management of data - SIGMOD '98
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After revealing the strong performance shortcomings of the state-of-the-art algorithm for k-nearest neighbor search [Korn et al. 1996], we present a novel multi-step algorithm which is guaranteed to produce ...
For an increasing number of modern database applications, efficient support of similarity search becomes an important task. ...
Most of the available algorithms are tuned to efficiently support k-nearest neighbor queries for a fixed retrieval parameter k. ...
doi:10.1145/276304.276319
dblp:conf/sigmod/SeidlK98
fatcat:mktlcsod5nhsbaa3licv3cn4wy
An efficient nearest neighbor search in high-dimensional data spaces
2002
Information Processing Letters
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[7] proposed an algorithm for a nearest neighbor search in the R-tree. ...
Introduction Similarity search in multimedia databases requires an efficient support of nearest neighbor search on a large set of high-dimensional points. ...
doi:10.1016/s0020-0190(01)00236-8
fatcat:7folunnj55g7jnbbzk2hpnp3be
Optimal multi-step k-nearest neighbor search
1998
SIGMOD record
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After revealing the strong performance shortcomings of the state-of-the-art algorithm for k-nearest neighbor search [Korn et al. 1996], we present a novel multi-step algorithm which is guaranteed to produce ...
For an increasing number of modern database applications, efficient support of similarity search becomes an important task. ...
Most of the available algorithms are tuned to efficiently support k-nearest neighbor queries for a fixed retrieval parameter k. ...
doi:10.1145/276305.276319
fatcat:hbqyc4rlpvctrblbrg2lfyscqa
A Trajectory Privacy Preserving Scheme in the CANNQ Service for IoT
2019
Sensors
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Furthermore, an aggregate nearest neighbor query algorithm based on strategy optimization, is adopted, to minimize the overhead of the LSP. ...
'Aggregate nearest neighbor query' is a new type of location-based query which asks the question, 'what is the best location for a given group of people to gather?' ...
Third, it is feasible to improve the response speed of the queries by improving the ANN query algorithm, but there is a lack of an efficient method for computing the aggregate nearest neighbors. ...
doi:10.3390/s19092190
fatcat:73wfdz5pqzfplj3foswlzykdly
DART: An Efficient Method for Direction-Aware Bichromatic Reverse k Nearest Neighbor Queries
[chapter]
2013
Lecture Notes in Computer Science
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We formally define the DBRkNN query, and then propose an efficient algorithm, called DART, for processing the DBRkNN query. ...
We adopt a filter-refinement framework that is widely used in many algorithms for reverse nearest neighbor queries. ...
objects that have q within k nearest neighbors (k is a positive integer, typically small). ...
doi:10.1007/978-3-642-40235-7_17
fatcat:msv24jy6f5extlqrlvw76q66pq
Voronoi Partition to Support Data Search in Uncertain Database with k-Bound Filtering
2020
Journal of Computer Science
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For this uncertain database, the important query method is Probabilistic k-Nearest Neighbor query (PkNN), which calculates the probability of the set of k objects to be closest to the given query point ...
In this study, we propose a method called voronoi partitioning to support searching in uncertain database (Partition threshold k Aggregate Nearest Neighbor query method-Partition_PANN). ...
Author's Contributions Slamet Sudaryanto Nurhendratno: Is involved in the concept of developing a search method, testing and analyzing results. ...
doi:10.3844/jcssp.2020.1753.1764
fatcat:s54uj4ohibdulc7ssqxeii4ozu
Finding Top-k Optimal Sequenced Routes -- Full Version
[article]
2018
arXiv
pre-print
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In addition, we demonstrate the high extensibility of the proposed algorithms by incorporating Hop Labeling, an effective label indexing technique for shortest path queries, to further improve efficiency ...
In StarKOSR, we further improve the efficiency by extending routes in an A* manner. ...
In this way, the i-th nearest neighbor in a category can be identified efficiently in an on-line manner by simply looking up the inverted label index. ...
arXiv:1802.08014v1
fatcat:to7mryaz4vbolhcveoba5whdd4
K-NN query algorithm based on PB-tree with the parallel lines division
2012
Communications in Mobile Computing
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Spatial index and query are enabling techniques for achieving the vision of the Internet of Things. K-NN is an algorithm which is used widely in spatial database. ...
Based on the study of previous algorithms, this paper proposes a novel K-NN query algorithm based on PB-tree with the parallel lines division. ...
Acknowledgements This work was supported by the Fundamental Research Funds for the Central Universities (China University of Geosciences at Beijing). ...
doi:10.1186/2192-1121-1-10
fatcat:omtmv7uswrevxg74feelncvzke
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