How to Efficiently Diagnose and Repair Fuzzy Database Queries that Fail

Olivier Pivert 1 Grégory Smits 1
1 SHAMAN - Symbolic and Human-centric view of dAta MANagement
IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Telling the user that there is no result for his/her query is very poorly informative and corresponds to the kind of situation cooperative systems try to avoid. Cooperative systems should rather explain the reason(s) of the failure, materialized by Minimal Failing Subqueries (MFS), and build alternative succeeding queries, called maXimal Succeeding Subqueries (XSS), that are as close as possible to the original query. In the particular context of fuzzy querying, we propose an efficient unified approach to the computation of gradual MFSs and XSSs that relies on a fuzzy-cardinality-based summary of the relevant part of the database.
Type de document :
Chapitre d'ouvrage
Fifty Years of Fuzzy Logic and its Applications, 326, Springer, pp.499-517, 2015, Studies in Fuzziness and Soft Computing, 〈10.1007/978-3-319-19683-1_25〉
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https://hal.inria.fr/hal-01186515
Contributeur : Olivier Pivert <>
Soumis le : mardi 25 août 2015 - 10:28:58
Dernière modification le : mercredi 29 novembre 2017 - 15:42:00

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Olivier Pivert, Grégory Smits. How to Efficiently Diagnose and Repair Fuzzy Database Queries that Fail. Fifty Years of Fuzzy Logic and its Applications, 326, Springer, pp.499-517, 2015, Studies in Fuzziness and Soft Computing, 〈10.1007/978-3-319-19683-1_25〉. 〈hal-01186515〉

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