基于P2P的自适应分布式k最近邻搜索算法

P2P-based Self-adaptive Distributed k-nearest Neighbor Search Algorithm

k最近邻搜索算法无法满足数据挖掘的分布性、实时性和可扩展性要求,针对该问题提出基于P2P的自适应分布式k最近邻搜索算法[0](P2PAKNNs)。阐述GHT*结构,定义高维数据相似度函数HDSF(X,Y),论述GHT*中的插入算法、范围查找算法和搜索算法。给出P2PAKNNs的实现过程,通过实验证明其正确性。

k-nearest Neighbor search algorithm（KNNs） can not satisfy the needs of distributing, real time performance and expansibility for data mining. Aiming at this problem, a P2P-based self-adaptive distributed KNNs（P2PAKNNs） is proposed. This paper expounds GHT＊ structure, and gives similarity measure function HDSF（X, Y）. Insert algorithm, range find algorithm and search algorithm in GHT＊ are discussed. Implementation process of P2PAKNNs is given, and its correctness is validated by experiment.