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

대용량 위치 데이터에서 효율적인 k-최근접 질의 처리 기법

  • 최도진 (충북대학교 정보통신공학과) ;
  • 임종태 (충북대학교 정보통신공학과) ;
  • 유승훈 (충북대학교 정보통신공학과) ;
  • 복경수 (충북대학교 정보통신공학과) ;
  • 유재수 (충북대학교 정보통신공학과)
  • Received : 2017.07.18
  • Accepted : 2017.08.04
  • Published : 2017.08.28

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

Acknowledgement

Grant : 초고성능컴퓨팅기반 건강한 고령사회 대응 빅데이터 분석기술개발

Supported by : 정보통신기술진흥센터, 한국과학기술정보연구원, 한국연구재단

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