期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2013
卷号：6
期号：2
出版社：SERSC
摘要：As an important decision support query, Group Nearest Neighbor (GNN) query has received considerable attention from Location Based Service (LBS) research community. Previous works paid much attention to the uncertain data objects (P). Nevertheless, very little work has done to the scenario when query objects (Q) are also uncertain. In this paper, The Range-based Probabilistic Group Nearest Neighbor (in short RP-GNN) query is introduced to draw a comprehensive discussion for this extended scenario. Two novel pruning methods are proposed to improve the performance of RP-GNN. The effectiveness, efficiency and scalability of proposed methods are validated through extensive experiments. The proposed methods achieve an average speed-up of 62.2% against existing probabilistic GNN algorithms and 1-2 orders of magnitude against linear scan
关键词：Range based queries; Probabilistic group nearest neighbor queries; Location ;based service
