Towards flexible querying of XML imprecise data in a dataware house opened on the web

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Abstract

This paper describes a new subsystem of the Sym'Previus knowledge base. This knowledge base contains information useful to helpexperts in the field of predictive microbiology. Information has several specific properties: it is incomplete, imprecise and heterogeneous. In thepre-existing Sym'Previus knowledge base, stable data are stored in a relational database and data which do not fit the relational structureare stored in a conceptual graph knowledge base. The MIEL language permits to scan simultaneously both bases in a transparent way for theuser, using fuzzy queries. The new subsystem described in the paper contains information found on the Web to complete the knowledge base. This information is stored in XML format. Firstly, we extend the XML model of the knowledge base to represent imprecise data as possibility distributions. Secondly, we present the mapping process used to translate a MIEL query into an XML query to scan the XML knowledge base.

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Buche, P., Dibie-Barthélemy, J., Haemmerlé, O., & Houhou, M. (2004). Towards flexible querying of XML imprecise data in a dataware house opened on the web. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3055, pp. 28–40). Springer Verlag. https://doi.org/10.1007/978-3-540-25957-2_4

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