The attention towards binary data coding increased consistently in the last decade due to
several reasons. The analysis of binary data characterizes several fields of application, such
as market basket analysis, DNA microarray data, image mining, text mining and web-
clickstream mining. The paper illustrates two different approaches exploiting a profitable
combination of clustering and dimensionality reduction for the identification of non-trivial
association structures in binary data. An application in the Association Rules framework …

A key element in the success of data analysis is the strong contribu-tion of visualization:
dendrograms and factorial plans are intuitive ways to display association relationships
within and among sets of variables and groups of units. In the Association Rules (AR) mining
we refer to an× p data matrix, where n indicates the number of statistical units and p the
number of attributes, which are also called items. The problem consists in analyzing links
between attributes. Sets of attributes that co-occur through the whole data matrix are referred …