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Indexing system and method for nearest neighbor searches in high dimensional data spaces

机译:高维数据空间中最近邻居搜索的索引系统和方法

摘要

Vectors representing objects in n-dimensional space are approximated by local polar coordinates on partitioned cells of the data space in response to a query, e.g., a query data vector entered with a request to find “k” nearest neighbors to the query vector. A set of candidate near neighbors is generated using the approximations, with the local polar coordinates being independent of the dimensionality of the data space. Then, an answer set of near neighbors is returned in response to the query. Thus, the present invention acts as a filter to reduce the number of actual data vectors in the data set that must be considered in responding to the query.
机译:响应于查询,表示n维空间中对象的向量由数据空间分区单元上的局部极坐标来近似,例如,输入查询数据向量并请求查找“ k”个最接近查询向量的邻居。使用近似值生成一组候选近邻,其中局部极坐标与数据空间的维数无关。然后,响应于该查询,返回近邻的答案集。因此,本发明充当过滤器,以减少响应查询时必须考虑的数据集中的实际数据向量的数量。

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