Efficient exact k-flexible aggregate nearest neighbor search in road networks using the M-treeopen access
- Authors
- Chung, Moonyoung; Hyun, Soon J.; Loh, Woong-Kee
- Issue Date
- Sep-2022
- Publisher
- SPRINGER
- Keywords
- Flexible aggregate nearest neighbor; Road networks; Exact search; Incremental Euclidean restriction
- Citation
- JOURNAL OF SUPERCOMPUTING, v.78, no.14, pp.16286 - 16302
- Journal Title
- JOURNAL OF SUPERCOMPUTING
- Volume
- 78
- Number
- 14
- Start Page
- 16286
- End Page
- 16302
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/85466
- DOI
- 10.1007/s11227-022-04496-2
- ISSN
- 0920-8542
- 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.
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