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Journal Article
Efficient exact k-flexible aggregate nearest neighbor search in road networks using the M-tree
- Authors
- Moonyoung Chung, Soon J. Hyun, Woong-Kee Loh
- Issue Date
- 2022-09
- Citation
- Journal of Supercomputing, v.78, no.14, pp.16286-16302
- ISSN
- 0920-8542
- Publisher
- Springer
- Language
- English
- Type
- Journal Article
- Abstract
- This study proposes an efficient exact k-flexible aggregate nearest neighbor (k-FANN) search algorithm in road networks using the M-tree. The state-of-the-art IER-kNN algorithm used the R-tree and pruned off unnecessary nodes based on the Euclidean coordinates of objects in road networks. However, IER-kNN made many unnecessary accesses to index nodes since the Euclidean distances between objects are significantly different from the actual shortest-path distances between them. In contrast, our algorithm proposed in this study can greatly reduce unnecessary accesses to index nodes compared with IER-kNN since the M-tree is constructed based on the actual shortest-path distances between objects. To the best of our knowledge, our algorithm is the first exact FANN algorithm that uses the M-tree. We prove that our algorithm does not cause any false drop. In conducting a series of experiments using various real road network datasets, our algorithm consistently outperformed IER-kNN by up to 6.92 times.
- KSP Keywords
- Aggregate nearest neighbor, KNN algorithm, R-Tree, Road networks, Search Algorithm(GSA), euclidean distance, nearest neighbor(NN), nearest neighbor search, shortest path, state-of-The-Art
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
