Efficient Iϵ/I-Approximate Ik/I-Flexible Aggregate Nearest Neighbor Search for Arbitrary Iϵ/I in Road Networks

Recently, complicated spatial search algorithms have emerged as spatial-information-based applications, such as location-based services (LBS), and have become very diverse and frequent. The aggregate nearest neighbor (ANN) search is an extension of the existing nearest neighbor (NN) search; it finds...

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Veröffentlicht in:Electronics (Basel) 2023-08, Vol.12 (17)
Hauptverfasser: Kwon, Hyuk-Yoon, Yoo, Jaejun, Loh, Woong-Kee
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Loh, Woong-Kee
description Recently, complicated spatial search algorithms have emerged as spatial-information-based applications, such as location-based services (LBS), and have become very diverse and frequent. The aggregate nearest neighbor (ANN) search is an extension of the existing nearest neighbor (NN) search; it finds the object p[sup.*] that minimizes G{d(p[sup.*] ,q[sub.i] ),q[sub.i] ∈Q} from a set Q of M (≥1) query objects, where G is an aggregate function and d() is the distance between two objects. The flexible aggregate nearest neighbor (FANN) search is an extension of the ANN search by introducing flexibility factor ϕ (0
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The aggregate nearest neighbor (ANN) search is an extension of the existing nearest neighbor (NN) search; it finds the object p[sup.*] that minimizes G{d(p[sup.*] ,q[sub.i] ),q[sub.i] ∈Q} from a set Q of M (≥1) query objects, where G is an aggregate function and d() is the distance between two objects. The flexible aggregate nearest neighbor (FANN) search is an extension of the ANN search by introducing flexibility factor ϕ (0&lt;ϕ≤1); it finds the object p[sup.*] that minimizes G{d(p[sup.*] ,q[sub.i] ),q[sub.i] ∈Q[sub.ϕ] } from Q[sub.ϕ] , a subset of Q with |Q[sub.ϕ] |=ϕ|Q|. This paper proposes an efficient ϵ-approximate k-FANN (k≥1) search algorithm for an arbitrary approximation ratio ϵ (≥1) in road networks. In general, ϵ-approximate algorithms are expected to give an improved search performance at the cost of allowing an error ratio of up to the given ϵ. 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subjects Algorithms
Location-based systems
Neural networks
Roads
South Korea
Streets
title Efficient Iϵ/I-Approximate Ik/I-Flexible Aggregate Nearest Neighbor Search for Arbitrary Iϵ/I in Road Networks
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