The paper discusses the benefit of using fuzzy sets in data summaries based on generalized association rules. Fuzzy sets provide a convenient interface between labels and data and allow for partial belonging to connex but distinct classes. They thus offer a robust reading of the data. Starting with fuzzy partitions of attribute domains which are meaningful for a user, a procedure is described which enables data summaries involving fuzzy quantifiers to be built, by computing fuzzy cardinalities. The difference between this new type of fuzzy summary and previous proposals is also pointed out.