Abstract
In this paper, we introduce a novel query type, the moving view field nearest neighbor (MVFNN) query —a continuous version of the view field nearest neighbor (VFNN) query. This query continuously retrieves the nearest object in the query's view field taking into account the changes of the query location and view field. In order to improve the performance of the query processing, we propose the notion of geographical and angular safe boundaries. We can skip redundant computation if the moved query satisfies the geographical and angular safe boundaries. Our method is easily applicable to existing services since we do not transform the general index structures. We prove the efficiency of our method by a series of experiments varying the parameters such as query's moving speed, view field angle, and the distribution of data objects.
| Original language | English |
|---|---|
| Journal | Data and Knowledge Engineering |
| DOIs | |
| Publication status | Accepted/In press - 2018 Jan 1 |
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Keywords
- Augmented reality
- Continuous query
- Location-based service
- Moving view field nearest neighbor query
- Spatial databases
ASJC Scopus subject areas
- Information Systems and Management
Cite this
Moving view field nearest neighbor queries. / Kim, Wooil; Shim, Changbeom; Heo, Wan; Yi, Sungmin; Chung, Yon Dohn.
In: Data and Knowledge Engineering, 01.01.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Moving view field nearest neighbor queries
AU - Kim, Wooil
AU - Shim, Changbeom
AU - Heo, Wan
AU - Yi, Sungmin
AU - Chung, Yon Dohn
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this paper, we introduce a novel query type, the moving view field nearest neighbor (MVFNN) query —a continuous version of the view field nearest neighbor (VFNN) query. This query continuously retrieves the nearest object in the query's view field taking into account the changes of the query location and view field. In order to improve the performance of the query processing, we propose the notion of geographical and angular safe boundaries. We can skip redundant computation if the moved query satisfies the geographical and angular safe boundaries. Our method is easily applicable to existing services since we do not transform the general index structures. We prove the efficiency of our method by a series of experiments varying the parameters such as query's moving speed, view field angle, and the distribution of data objects.
AB - In this paper, we introduce a novel query type, the moving view field nearest neighbor (MVFNN) query —a continuous version of the view field nearest neighbor (VFNN) query. This query continuously retrieves the nearest object in the query's view field taking into account the changes of the query location and view field. In order to improve the performance of the query processing, we propose the notion of geographical and angular safe boundaries. We can skip redundant computation if the moved query satisfies the geographical and angular safe boundaries. Our method is easily applicable to existing services since we do not transform the general index structures. We prove the efficiency of our method by a series of experiments varying the parameters such as query's moving speed, view field angle, and the distribution of data objects.
KW - Augmented reality
KW - Continuous query
KW - Location-based service
KW - Moving view field nearest neighbor query
KW - Spatial databases
UR - http://www.scopus.com/inward/record.url?scp=85058820286&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058820286&partnerID=8YFLogxK
U2 - 10.1016/j.datak.2018.12.002
DO - 10.1016/j.datak.2018.12.002
M3 - Article
AN - SCOPUS:85058820286
JO - Data and Knowledge Engineering
JF - Data and Knowledge Engineering
SN - 0169-023X
ER -