  This paper presents a study of the characteristics of transactional databases
used in frequent itemset mining. Such characterizations have typically been
used to benchmark and understand the data mining algorithms working on these
databases. The aim of our study is to give a picture of how diverse and
representative these benchmarking databases are, both in general but also in
the context of particular empirical studies found in the literature. Our
proposed list of metrics contains many of the existing metrics found in the
literature, as well as new ones. Our study shows that our list of metrics is
able to capture much of the datasets' inner complexity and thus provides a good
basis for the characterization of transactional datasets. Finally, we provide a
set of representative datasets based on our characterization that may be used
as a benchmark safely.
