Efficient Shared Execution Processing of k-Nearest Neighbor Joins in Road Networks
Author
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-12
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Telecommunications Engineering
Abstract EN
We investigate the k-nearest neighbor (kNN) join in road networks to determine the k-nearest neighbors (NNs) from a dataset S to every object in another dataset R.
The kNN join is a primitive operation and is widely used in many data mining applications.
However, it is an expensive operation because it combines the kNN query and the join operation, whereas most existing methods assume the use of the Euclidean distance metric.
We alternatively consider the problem of processing kNN joins in road networks where the distance between two points is the length of the shortest path connecting them.
We propose a shared execution-based approach called the group-nested loop (GNL) method that can efficiently evaluate kNN joins in road networks by exploiting grouping and shared execution.
The GNL method can be easily implemented using existing kNN query algorithms.
Extensive experiments using several real-life roadmaps confirm the superior performance and effectiveness of the proposed method in a wide range of problem settings.
American Psychological Association (APA)
Cho, Hyung-Ju. 2018. Efficient Shared Execution Processing of k-Nearest Neighbor Joins in Road Networks. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1204644
Modern Language Association (MLA)
Cho, Hyung-Ju. Efficient Shared Execution Processing of k-Nearest Neighbor Joins in Road Networks. Mobile Information Systems No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1204644
American Medical Association (AMA)
Cho, Hyung-Ju. Efficient Shared Execution Processing of k-Nearest Neighbor Joins in Road Networks. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1204644
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204644