  The use of Pearson's correlation coefficient in Author Cocitation Analysis
was compared with Salton's cosine measure in a number of recent contributions.
Unlike the Pearson correlation, the cosine is insensitive to the number of
zeros. However, one has the option of applying a logarithmic transformation in
correlation analysis. Information calculus is based on both the logarithmic
transformation and provides a non-parametric statistics. Using this methodology
one can cluster a document set in a precise way and express the differences in
terms of bits of information. The algorithm is explained and used on the data
set which was made the subject of this discussion.
