Earticle

초록

영어

Range-based Probabilistic Group Nearest Neighbor (in short RP-GNN) query has recently gain much attention, due to its wide usage in many Location Based Services (LBSs). Previous works mainly focus on the uncertainty of data objects (P). While the uncertainty of query objects (Q) is prevailing in reality. In this paper, a comprehensive discussion on uncertain query objects is presented. Meanwhile two novel pruning methods are proposed to improve the performance of RP-GNN: one is Query points pruning (Q_pruning) and the other is Geometric pruning (G_pruning). Q_pruning reduces the number of query objects needed to be considered. And G_pruning method exploits the geometric properties of the RP-GNN problem to narrow down the search space. Extensive experiments show the effectiveness, efficiency and scalability of proposed methods.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Formal Definition of the Problem
 4. RP-GNN with Uncertain Query Objects
  4.1 Q_pruning
  4.2 G_pruning
  4.3 Procedure of RP-GNN
 5. Performance Evaluation
  5.1 Experiment Results
 6. Conclusions
 References

키워드

저자

• Peng Chen [ Department of Computer Science and Technology, East China Normal University, 200241 Shanghai, China ]
• Junzhong Gu [ Department of Computer Science and Technology, East China Normal University, 200241 Shanghai, China ]
• Xin Lin [ Department of Computer Science and Technology, East China Normal University, 200241 Shanghai, China ]
• Rong Tan [ Department of Computer Science and Technology, East China Normal University, 200241 Shanghai, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605