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Journal Article
α-Probabilistic Flexible Aggregate Nearest Neighbor Search in Road Networks using Landmark Multidimensional Scaling
- Authors
- Moonyoung Chung, Woong-Kee Loh
- Issue Date
- 2021-02
- Citation
- Journal of Supercomputing, v.77, no.2, pp.2138-2153
- ISSN
- 0920-8542
- Publisher
- Springer
- Language
- English
- Type
- Journal Article
- Abstract
- In spatial database and road network applications, the search for the nearest neighbor (NN) from a given query object q is the most fundamental and important problem. Aggregate nearest neighbor (ANN) search is an extension of the NN search with a set of query objects Q= { q, ?떙 , qM-1} and finds the object p?닓 that minimizes g{ d(p?닓, qi) , qi?늿 Q} , where g (max or sum) is an aggregate function and d() is a distance function between two objects. Flexible aggregate nearest neighbor (FANN) search is an extension of the ANN search with the introduction of a flexibility factor ??(0
- KSP Keywords
- ANN search, Aggregate function, Aggregate nearest neighbor, Distance-based, Euclidean space, Higher performance, Multi-dimensional scaling(MDS), Network applications, Network objects, Performance comparison, R-Tree
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
