In this paper we propose an extension of Factor PD-clustering for simultaneous
classification of rows and columns of frequency matrices extracted from large
textual datasets. The aim is to extract information from documents usually produced
and that are not used because of their special nature. The work is carried out within
the European project BLUE-ETS, which aims to provide tools for the construction
of robust and high quality official statistics for businesses
