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In this paper, a new approach to database summarization is introduced through our model named SAINTETIQ. Based on a hierarchical conceptual clustering algorithm, SAINTETIQ incrementally builds a summary hierarchy from database records. Furthermore, the fuzzy set-based representation of data allows to handle vague, uncertain or imprecise information, as well as to improve accuracy and robustness of the construction process of summaries. Finally, background knowledge provides a user-defined vocabulary to synthesize and to make highly intelligible the summary descriptions.