Abstract
With the increasing size of databases, the extraction of data summaries becomes more and more useful. The use of fuzzy sets seems interesting in order to extract linguistic summaries, i.e., statements from the natural language, containing gradual properties, which are meaningful for human operators. This paper focuses on the extraction from databases of linguistic summaries, using so-called fuzzy gradual rules, which encode statements of the form “the younger the employees, the smaller their bonus”. The summaries considered here are more on the relations between labels of the attributes than on the data themselves. The first idea is to extract all the rules which are not in contradiction with tuples of a given relation. Then, the interest of these rules is questioned. For instance, some of them can reveal potential incoherence, while other are not really informative. It is then shown that in some cases, interesting information can be extracted from these rules. Last, some properties the final set of rules should verify are outlined.
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© 1999 Springer-Verlag Berlin Heidelberg
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Bosc, P., Pivert, O., Ughetto, L. (1999). On Data Summaries Based on Gradual Rules. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_56
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DOI: https://doi.org/10.1007/3-540-48774-3_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
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