Towards Category-Based Fuzzy Querying of Both Structured and Semi-Structured Imprecise Data

International audienceThis work presents a part of a national project which aims at building a tool for the analysis of microbial risks in food products. As a first step, we propose a querying system using fuzzy values which must be compared to imprecise information stored in the database. This category-based unified querying system works in two steps. In the first one, the category of data concerned by the query is identified in order to build two queries which will be processed on two separate databases. In the second step, both previous queries scan simultaneously a relational database and a conceptual graph knowledge base, containing microbiological information; the results from the two scans are merged in a unique table format to be shown to the user. Fuzzy values and imprecise information are managed only in the relational database in this paper. It will be extended to conceptual graph knowledge base in a future paper