The relation between Pearson’s correlation coefficient r and Salton’s cosine measure

Abstract

The relation between Pearson’s correlation coefficient and Salton’s cosine measure is revealed based on the different possible values of the division of the -norm and the norm of a vector. These different values yield a sheaf of increasingly straight lines which form together a cloud of points, being the investigated relation. These theoretical results are tested against the author co-citation relations among 24 informetricians for who two matrices can be constructed, based on co-citations: the asymmetric occurrence matrix and the symmetric co-citation matrix. Both examples completely confirm the theoretical results. The results enable us to specify an algorithm which provides a threshold value for the cosine above which none of the corresponding Pearson correlations would be negative. Using this threshold value can be expected to optimize the visualization.