Study on dimensionality curse in the nearest neighbor queries based on statistics

This paper explores the effect of dimensionality on the “nearest neighbor” problem.Based on statistics,it shows that under some conditions,as dimensionality increases,the distances between query point and data points approach to each other.So the “nearest neighbor” is becoming meaningless.The way of how to evaluate the dimensionality effect is presented.From two distributions of statistics about distance,the effect of dimensionality on the “nearest neighbor” problem is evaluated.Empirical result is presented to demonstrate the two distributions.