Abstract
This 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.
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References
P. Bosc, L. Lietard, and O. Pivert. Soft querying, a new feature for database management system. In Proceedings DEXA’94 (Database and EXpert system Application), Lecture Notes in Computer Science #856, pages 631–640. Springer-Verlag, 1994.
H. Prade. Lipski’s approach to incomplete information data bases restated and generalized in the setting of zadeh’s possibility theory. Information Systems, 9 (1): 27–42, 1984.
J. Galindo, J.C. Cubero, O. Pons, and J.M. Medina. A server for fuzzy SQL queries. In Proceedings of the workshop FQAS’98 (Flexible Query-Answering Systems), pages 161–171, Roskilde, Denmark, May 1998.
S. Zadrozny and J. Kacprzyk. Implementing fuzzy querying via the internet/WWW: Java applets, activeX controls and cookies. In Proceedings of the workshop FQAS’98 (Flexible Query-Answering Systems), pages 358–369, Roskilde, Denmark, May 1998.
P. Buche and S. Loiseau. Using contextual fuzzy views to query imprecise data. In Proceedings DEXA ‘89 (Database and EXpert system Application), Lecture Notes in Computer Science #1677,pages 460–472, Florence, Italy, August 1999. Springer-Verlag.
S. Abiteboul, D. Quass, J. McHugh, J. Widom, and J. Wiener. The Lorel query language for semi-structured data. Journal of Digital Libraries, 1(1):???-???, November 1996.
S. Coulondre and T. Libourel. Viewpoints handling in a object model with criterium-based classes. In Proceedings DEXA ‘89 (Database and EXpert system Application),Lecture Notes in Computer Science #1677,pages 573–583, Florence, Italy, August 1999. Springer-Verlag.
A. Michard. XML, langage et applications, pages 335–344. Eyrolles, Paris, 1999.
R. Goldman, J. McHugh, and J. Widom. From semistructured data to XML: Migrating the lore data model and query language. In Proceedings of the 2nd International Workshop on the Web and Databases (WebDB ‘89),Philadelphia, USA, June 1999. Springer.
D. Dubois, H. Prade, and C. Testemale. Weighted fuzzy pattern matching. Fuzzy Sets and Systems, 28: 313–331, 1988.
S. Salotti. Filtrage flou et représentation centrée-objet pour raisonner par analogie: le système FLORAN. Thèse de doctorat, Université Paris XI Orsay, Décembre 1992.
D. Dubois and H. Prade. Fuzziness in Database Management Systems, P. Bosc and J. Kacprzyk eds., chapter Tolerant fuzzy pattern matching: an introduction, pages 42–58. Heidelberg: Physica Verlag, 1995.
H. Prade and C. Testemale. Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries. Information Sciences, 34: 115–143, 1984.
P. Bosc and O. Pivert. On the comparison of imprecise values in fuzzy databases. In Proceedings of FUZZ-IEEE’97, pages 707–712, Barcelona, Spain, 1997.
J.F. Sowa. Conceptual structures - Information processing in Mind and Machine. Addison-Welsey, 1984.
M.L. Mugnier and M. Chein. Représenter des connaissances et raisonner avec des graphes. Revue d’Intelligence Artificielle, 10 (1): 7–56, 1996.
M.L. Mugnier. On generalization/specialization for conceptual graphs. Journal of Experimental and Theoretical Artificial Intelligence, 7 (3): 325–344, 1995.
P. Buche and O. Haemmerlé. Vers un système unifié d’interrogation de données imprécises structurées et semi-structurées utilisant des vues floues. In Actes du XVIIIème Congrès INFORSID, pages 174–189, Lyon, France, Mai 2000.
O. Haemmerlé and O. Guinaldo. CoGITo v3.3: plate-forme de développement d’applications sur les graphes conceptuels. Technique et Science Informatiques, 18 (9): 933–965, Novembre 1999.
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Buche, P., Haemmerlé, O. (2001). Towards Category-Based Fuzzy Querying of Both Structured and Semi-Structured Imprecise Data. In: Larsen, H.L., Andreasen, T., Christiansen, H., Kacprzyk, J., Zadrożny, S. (eds) Flexible Query Answering Systems. Advances in Soft Computing, vol 7. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1834-5_33
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DOI: https://doi.org/10.1007/978-3-7908-1834-5_33
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