Towards Flexible Querying of XML Imprecise Data in a Dataware House Opened on the Web

Abstract

AbstractThis paper describes a new subsystem of the Sym’Previus knowledge base. This knowledge base contains information useful to help experts in the field of predictive microbiology. Information has several specific properties: it is incomplete, imprecise and heterogeneous. In the pre-existing Sym’Previus knowledge base, stable data are stored in a relational database and data which do not fit the relational structure are stored in a conceptual graph knowledge base. The MIEL language permits to scan simultaneously both bases in a transparent way for the user, 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.KeywordsKnowledge BaseData TreePossibility DistributionSelection AttributeImprecise DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.