Flexible bipolar querying of uncertain data using an ontology

Patrice Buche 1, 2 Sébastien Destercke 3 Valérie Guillard 2 Ollivier Haemmerlé 4 Rallou Thomopoulos 1, 2
1 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
2 UMR IATE - Ingénierie des Agro-polymères et Technologies Émergentes
3 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
4 IRIT - Institut de recherche en informatique de Toulouse
Abstract : In this paper, we propose an approach to query a database where the user preferences can be bipolar (i.e., express both constraints and wishes about the desired result) and the data stored in the database can be uncertain. Query results are then completely ordered with respect to these bipolar preferences, giving priority to constraints over wishes. Furthermore, we consider user preferences expressed on a domain of values which is not "flat", but contains values that are more specific than others according to the "kind of" relation. These preferences are represented by specific fuzzy sets, called "Hierarchical Fuzzy Sets" and defined over a simple ontology.We propose a use of "Hierarchical Fuzzy Sets" for query enlargement purposes. The approach is illustrated on a real-world problem concerning the selection of optimal packaging material for fresh fruits and vegetables. Patrice
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00764985
Contributor : Patrice Buche <>
Submitted on : Thursday, December 13, 2012 - 9:44:59 PM
Last modification on : Monday, April 29, 2019 - 4:48:44 PM

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Patrice Buche, Sébastien Destercke, Valérie Guillard, Ollivier Haemmerlé, Rallou Thomopoulos. Flexible bipolar querying of uncertain data using an ontology. Flexible Approaches in Data, Information and Knowledge Management, 467, Springer, pp.165-188, 2013, Studies in Computational Intelligence, ⟨10.1007/978-3-319-00954-4_8⟩. ⟨lirmm-00764985⟩

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