Abstract
The paper is dealing with the problem of flexible querying using vague linguistic expressions and user dependent requirements. We propose a solution based on incorporating weights into scoring rules by the usage of fuzzy logic and fuzzy similarities. We define a data model, which enables to answer queries over crisp data using fuzzy knowledge base, fuzzy interpretation of vague expressions and fuzzy similarities. We present an extension of a positive relational algebra and show that its the expressive power together with a fuzzy fixpoint operator is sufficient for evaluating fuzzy Datalog programs. We discuss also a computational model for queries with a threshold on truth values and optimization of such queries.
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Pokorný, J., Vojtáš, P. (2001). A Data Model for Flexible Querying. In: Caplinskas, A., Eder, J. (eds) Advances in Databases and Information Systems. ADBIS 2001. Lecture Notes in Computer Science, vol 2151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44803-9_22
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DOI: https://doi.org/10.1007/3-540-44803-9_22
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