Abstract
Incorporation of fuzziness into database systems allows to expand the analysis of data during the querying process. Approximate processing of data includes not only rows that exactly meet the search criteria, but also rows that are similar with the given range of tolerance. Queries formulated in natural language usually consist of imprecise and fuzzy terms. However, the implementation of the imprecision in query languages, such as SQL, requires additional extensions in a target database system. In the paper, we devote our attention to different methods of data grouping. In the first part of the paper we concentrate on the process of fuzzy grouping of crisp data. In the second part, we focus on the grouping of fuzzy data.
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Małysiak-Mrozek, B., Mrozek, D., Kozielski, S. (2009). Data Grouping Process in Extended SQL Language Containing Fuzzy Elements. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_25
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DOI: https://doi.org/10.1007/978-3-642-00563-3_25
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