Similarity Search Problem Research on Multi-dimensional Data Sets

Yong Shi, Brian Graham
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Abstract

In this paper, we present our continuous work on designing an algorithm to find nearest neighbors to given queries. In our previous work, we analyze the situation that there are multiple queries with different level of importance, and define a weight for each query point. We also propose an algorithm to find nearest neighbors to multiple queries with weights and enhanced our algorithm based on query point distribution. In this paper we analyze the data distribution on various dimensions, and apply the shrinking concept for the improvement and enhancement of our multi-query search approach.
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多维数据集的相似搜索问题研究
在本文中,我们展示了我们在设计一种算法来找到给定查询的最近邻居方面的持续工作。在之前的工作中,我们分析了存在多个重要程度不同的查询的情况,并为每个查询点定义了权重。我们还提出了一种带权重的多查询最近邻算法,并基于查询点分布对算法进行了改进。本文分析了数据在各个维度上的分布,并应用收缩的概念来改进和增强我们的多查询搜索方法。
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