Abstract
We study rules \(A \Longrightarrow B\) describing attribute dependencies in tables over domains with similarity relations. \(A \Longrightarrow B\) reads “for any two table rows: similar values of attributes from A imply similar values of attributes from B”. The rules generalize ordinary functional dependencies in that they allow for processing of similarity of attribute values. Similarity is modeled by reflexive and symmetric fuzzy relations. We show a system of Armstrong-like derivation rules and prove its completeness (two versions). Furthermore, we describe a non-redundant basis of all rules which are true in a data table and present an algorithm to compute bases.
Supported by grant No. 1ET101370417 of GA AV ČR, by grant No. 201/05/0079 of the Czech Science Foundation, and by institutional support, research plan MSM 6198959214.
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Bělohlávek, R., Vychodil, V. (2006). Data Tables with Similarity Relations: Functional Dependencies, Complete Rules and Non-redundant Bases. In: Li Lee, M., Tan, KL., Wuwongse, V. (eds) Database Systems for Advanced Applications. DASFAA 2006. Lecture Notes in Computer Science, vol 3882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11733836_45
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DOI: https://doi.org/10.1007/11733836_45
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