摘要
针对障碍空间中不确定对象的组k最近邻查询问题,提出了Pk OGNN(probabilistic k obstructed group nearest neighbor query)查询方法。Pk OGNN查询方法主要包括4个子算法:Compadist_o(),SpatialPru(),PruInterEnt()和PkOGNN(),这些子算法分别是集总障碍距离的计算方法、空间修剪方法、根据空间修剪方法进行R树中间结点修剪、最终精炼查询方法。所提Pk OGNN查询方法通过集成有效的修剪策略以便减少Pk OGNN的搜索空间,得到正确的k GNNs。理论研究和实验结果表明,所提方法具有较好的性能。
To deal with the problem of group k-nearest neighbor query method for uncertainty data in obstructed spaces,this paper presents the method of the Pk OGNN( probabilistic k obstructed group nearest neighbor) query.The Pk OGNN query method mainly includes four sub-algorithms: Compadist _o(),SpatialPru(),PruInterEnt()and PkOGNN(),These algorithms are respectively the calculation of the aggregate obstructed distance,the spatial pruning method,the pruning of the R-tree intermediate items according to the spatial pruning method,the final refined query method. It integrates the effective pruning methods to reduce the search space of Pk OGNN and get the correct k GNNs. The theoretical research and experimental results show that the proposed method has good efficiency.
引文
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