Nearest neighbors in high-dimensional data: the emergence and influence of hubs

  title={Nearest neighbors in high-dimensional data: the emergence and influence of hubs},
  author={Milos Radovanovic and Alexandros Nanopoulos and Mirjana Ivanovic},
High dimensionality can pose severe difficulties, widely recognized as different aspects of the curse of dimensionality. In this paper we study a new aspect of the curse pertaining to the distribution of k-occurrences, i.e., the number of times a point appears among the k nearest neighbors of other points in a data set. We show that, as dimensionality increases, this distribution becomes considerably skewed and hub points emerge (points with very high k-occurrences). We examine the origin of… CONTINUE READING
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