  This paper proposes to perform authorship analysis using the Fast Compression
Distance (FCD), a similarity measure based on compression with dictionaries
directly extracted from the written texts. The FCD computes a similarity
between two documents through an effective binary search on the intersection
set between the two related dictionaries. In the reported experiments the
proposed method is applied to documents which are heterogeneous in style,
written in five different languages and coming from different historical
periods. Results are comparable to the state of the art and outperform
traditional compression-based methods.
