Using Contextual Fuzzy Views to Query Imprecise Data

Buche, Patrice; Loiseau, Sylvain

doi:10.1007/3-540-48309-8_43

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…In the following, we present an original fuzzy query processing strategy relying on the use of fuzzy views. The use of fuzzy views has already been advocated in the literature to evaluate fuzzy queries, see [7], [10], [11], [13]. However, in all of these works, the fuzzy views considered correspond either to predicates of a predefined expert vocabularywhereas we consider end-user-defined fuzzy terms -or to previously executed queries.…”

Section: B About Fuzzy Query Processing: Related Workmentioning

confidence: 99%

Processing Fuzzy Relational Queries Using Fuzzy Views

Doumard

Pivert

Smits

et al. 2019

2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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This paper proposes two original approaches to the processing of fuzzy queries in a relational database context. The general idea is to use views, either materialized or not. In the first case, materialized views are used to store the satisfaction degrees related to user-defined fuzzy predicates, instead of calculating them at runtime by means of user functions embedded in the query (which induces an important overhead). In the second case, abstract views are used to efficiently access the tuples that belong to the α-cut of the query result, by means of a derived Boolean selection condition.

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Section: B About Fuzzy Query Processing: Related Workmentioning

confidence: 99%

Processing Fuzzy Relational Queries Using Fuzzy Views

Doumard

Pivert

Smits

et al. 2019

2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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“…This database is enquired through the web-based browser called MIEL (Figure 2), a multicriterion system, specifically developed for this database and performing fuzzy querying thanks to an additional knowledge discussed in Buche et Loiseau (1999) and Buche et al (2002). MIEL crosses the user demand about food, micro-organism and environmental factors.…”

Section: A Relational Database Of Food Microbiologymentioning

confidence: 99%

The “Sym'Previus” software, a tool to support decisions to the foodstuff safety

Leporq¹,

Membré²,

Dervin

et al. 2005

International Journal of Food Microbiology

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Describing the Sym'Previus project, the software and its deliverable facilities is the aim of this present paper. This software concerns all the partners of the food industry who are involved in the management of food safety and allows food-borne pathogen behaviour in food to be predicted, as function of the environment (nature of the food, manufacturing process, conditions of conservation). This analysis of microbial behaviour has been possible thanks to the progress made in predictive microbiology since the 1980s. Sym'Previus offers to food industry professionals and their partners the possibility of applying this progress, by giving access to a database, to simulation systems and expertise.

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“…A second reason is that it has been widely studied in previous researches as a way of managing fuzzy queries and imprecise information, operated in the SI engine. The structured information subsystem of UQS is presented in [4].…”

Section: Introductionmentioning

confidence: 99%

Representation of semi-structured imprecise data for fuzzy querying

Buche¹,

Haemmerlé²,

Thomopoulos³

Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)

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tel : +33 1 44 08 16 75, +33 1 44 08 72 29, +33 1 44 08 16 79, fax : +33 1 44 08 16 66 e-mail : { Patrice.Buche,Ollivier.Haemmerle,Rallou.Thomopoulos} AbstractThis work is 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 unified querying system which simultaneously scans two complementary bases, containing microbiological information : a relational database containing structured information and a conceptual graph knowledge base containing semi-structured information. The unified querying system sends the user's query to both of them. Fuzzy queries and imprecise information are handled in both bases. To achieve this goal, we propose a way of representing fuzzy values, including numerical values, in conceptual graphs.

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Using Contextual Fuzzy Views to Query Imprecise Data

Cited by 5 publications

References 14 publications

Processing Fuzzy Relational Queries Using Fuzzy Views

Processing Fuzzy Relational Queries Using Fuzzy Views

The “Sym'Previus” software, a tool to support decisions to the foodstuff safety

Representation of semi-structured imprecise data for fuzzy querying

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