  In this paper we apply different techniques of information distortion on a
set of classical books written in English. We study the impact that these
distortions have upon the Kolmogorov complexity and the clustering by
compression technique (the latter based on Normalized Compression Distance,
NCD). We show how to decrease the complexity of the considered books
introducing several modifications in them. We measure how the information
contained in each book is maintained using a clustering error measure. We find
experimentally that the best way to keep the clustering error is by means of
modifications in the most frequent words. We explain the details of these
information distortions and we compare with other kinds of modifications like
random word distortions and unfrequent word distortions. Finally, some
phenomenological explanations from the different empirical results that have
been carried out are presented.
