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AnswerPairs and Processing of Continuous Nearest Neighbor Queries *
"... International University ..."
Range nearestneighbor query
 IEEE Transactions on Knowledge and Data Engineering (TKDE
"... A range nearestneighbor (RNN) query retrieves the nearest neighbor (NN) for every point in a range. It is a natural generalization of point and continuous nearestneighbor queries and has many applications. In this paper, we consider the ranges as (hyper)rectangles and propose efficient inmemory ..."
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Cited by 40 (2 self)
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A range nearestneighbor (RNN) query retrieves the nearest neighbor (NN) for every point in a range. It is a natural generalization of point and continuous nearestneighbor queries and has many applications. In this paper, we consider the ranges as (hyper)rectangles and propose efficient in
Nearestneighbor Queries in Probabilistic Graphs
"... Abstract — Large probabilistic graphs arise in various domains spanning from social networks to biological and communication networks. An important query in these graphs is the k nearestneighbor query, which involves finding and reporting the k closest nodes to a specific node. This query assumes th ..."
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Cited by 3 (0 self)
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are computationally intractable to compute exactly. Thus, in order to process nearestneighbor queries, we resort to Monte Carlo sampling and exploit novel graphtransformation ideas and pruning opportunities. In our extensive experimental analysis, we explore the tradeoffs of our approximation algorithms
When Is "Nearest Neighbor" Meaningful?
 In Int. Conf. on Database Theory
, 1999
"... . We explore the effect of dimensionality on the "nearest neighbor " problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance ..."
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Cited by 402 (1 self)
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. We explore the effect of dimensionality on the "nearest neighbor " problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches
Continuous Nearest Neighbor Search
, 2002
"... 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 <point, interval> tuples, such that point is the NN of all po ..."
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Cited by 159 (10 self)
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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 <point, interval> tuples, such that point is the NN of all
Densitybased indexing for approximate nearestneighbor queries
 In Proc. KDD
, 1999
"... We consider the problem of performing Nearestneighbor queries efficiently over large highdimensional databases. To avoid a full database scan, we target constructing a multidimensional index structure. It is wellaccepted that traditional database indexing algorithms fail for highdimensional data ..."
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Cited by 35 (2 self)
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We consider the problem of performing Nearestneighbor queries efficiently over large highdimensional databases. To avoid a full database scan, we target constructing a multidimensional index structure. It is wellaccepted that traditional database indexing algorithms fail for high
NearestNeighbor Searching Under Uncertainty
, 2012
"... Nearestneighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition, and ..."
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Cited by 17 (7 self)
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Nearestneighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition
Two Algorithms for NearestNeighbor Search in High Dimensions
, 1997
"... Representing data as points in a highdimensional space, so as to use geometric methods for indexing, is an algorithmic technique with a wide array of uses. It is central to a number of areas such as information retrieval, pattern recognition, and statistical data analysis; many of the problems aris ..."
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Cited by 201 (0 self)
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arising in these applications can involve several hundred or several thousand dimensions. We consider the nearestneighbor problem for ddimensional Euclidean space: we wish to preprocess a database of n points so that given a query point, one can efficiently determine its nearest neighbors
Moving Convolutions and . . . NearestNeighbor Queries for Uncertain Trajectories
, 2009
"... This report presents our solution to the problem of processing continuous Nearest Neighbor (NN) queries for moving objects trajectories when the exact position of a given object at a particular time instant is not known, but is bounded by an uncertainty region. As has already been observed in the li ..."
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This report presents our solution to the problem of processing continuous Nearest Neighbor (NN) queries for moving objects trajectories when the exact position of a given object at a particular time instant is not known, but is bounded by an uncertainty region. As has already been observed
NearestNeighbor Searching Under Uncertainty
, 2012
"... Nearestneighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition, and ..."
Abstract
 Add to MetaCart
Nearestneighbor queries, which ask for returning the nearest neighbor of a query point in a set of points, are important and widely studied in many fields because of a wide range of applications. In many of these applications, such as sensor databases, location based services, face recognition
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