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Proceedings of the 2006 ACM SIGMOD international conference on Management of data
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In this paper, we present continuous research on data analysis based on our previous work on similarity search problems. PanKNN [13] is a novel technique which explores the meaning of K nearest neighbors from a new perspective, redefines the distances between data points and a given query point Q, and efficiently and effectively selects data points which are closest to Q. It can be applied in various data mining fields. In this paper, we present our approach to improving the PanKNN algorithm using the Shrinking concept. Shrinking[15] is a data preprocessing technique which optimizes the inner structure of data inspired by the Newton's Universal Law of Gravitation[11] in the real world. This improved approach can assist to improve the performance of existing data analysis approaches.