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Querying a database with fuzzy attribute values by iterative updating of the selection criteria

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Fuzzy Logic in Artificial Intelligence (FLAI 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 847))

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Abstract

With multimedia now a commercial reality the need for more flexible forms of data retrieval is again becoming important. We introduce the need for fuzzy features to describe pictures or sounds such that a database querying system may select a subset of the database entries which conform to vague descriptions of multimedia data objects. We suggest that an iterative style of querying is important to fuzzy querying and is consistent with human conversation where a dialogue between two parties provides a clearer solution than as a result of a monologue. We introduce the concept of semantic unification to provide a fuzzy feature matching facility as well as evidential support logic to combine the solutions for a series of features. Finally we demonstrate the theory with a small database of British mammals interpreting the solutions and showing the facilities that fuzzy querying can allow.

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Anca L. Ralescu

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© 1994 Springer-Verlag Berlin Heidelberg

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Baldwin, J.F., Coyne, M.R., Martin, T.P. (1994). Querying a database with fuzzy attribute values by iterative updating of the selection criteria. In: Ralescu, A.L. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1993. Lecture Notes in Computer Science, vol 847. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58409-9_6

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  • DOI: https://doi.org/10.1007/3-540-58409-9_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58409-4

  • Online ISBN: 978-3-540-48780-7

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