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http://dx.doi.org/10.5392/JKCA.2017.17.08.619

Efficient k-Nearest Neighbor Query Processing Method for a Large Location Data  

Choi, Dojin (충북대학교 정보통신공학과)
Lim, Jongtae (충북대학교 정보통신공학과)
Yoo, Seunghun (충북대학교 정보통신공학과)
Bok, Kyoungsoo (충북대학교 정보통신공학과)
Yoo, Jaesoo (충북대학교 정보통신공학과)
Publication Information
The Journal of the Korea Contents Association / v.17, no.8, 2017 , pp. 619-630 More about this Journal
Abstract
With the growing popularity of smart devices, various location based services have been providing to users. Recently, some location based social applications that combine social services and location based services have been emerged. The demands of a k-nearest neighbors(k-NN) query which finds k closest locations from a user location are increased in the location based social network services. In this paper, we propose an approximate k-NN query processing method for fast response time in a large number of users environments. The proposed method performs efficient stream processing using big data distributed processing technologies. In this paper, we also propose a modified grid index method for indexing a large amount of location data. The proposed query processing method first retrieves the related cells by considering a user movement. By doing so, it can make an approximate k results set. In order to show the superiority of the proposed method, we conduct various performance evaluations with the existing method.
Keywords
Stream Processing; Continuos Query Processing; Approximate k-NN; LBS; Moving Object;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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