Fuzzy semantic tagging and flexible querying of XML documents extracted from the Web
Journal of Intelligent Information Systems
Fuzzy Sets Defined on a Hierarchical Domain
IEEE Transactions on Knowledge and Data Engineering
The MIEL system: Uniform interrogation of structured and weakly-structured imprecise data
Journal of Intelligent Information Systems
An weighted ontology-based semantic similarity algorithm for web service
Expert Systems with Applications: An International Journal
Flexible SPARQL Querying of Web Data Tables Driven by an Ontology
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Fuzzy concepts applied to the design of a database in predictive microbiology
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Semantic annotation of data tables using a domain ontology
DS'07 Proceedings of the 10th international conference on Discovery science
An ontology-driven annotation of data tables
WISE'07 Proceedings of the 2007 international conference on Web information systems engineering
The MIEL++ architecture when RDB, CGs and XML meet for the sake of risk assessment in food products
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Approximate querying of XML fuzzy data
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Genetic fuzzy markup language for game of NoGo
Knowledge-Based Systems
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In this paper, we present a new method, called multiview fuzzy querying, which permits to query incomplete, imprecise and heterogeneously structured data stored in a relational database. This method has been implemented in the MIEL software. MIEL is used to query the Sym'Previus database which gathers information about the behavior of pathogenic germs in food products. In this database, data are incomplete because information about all possible food products and all possible germs is not available; data are heterogeneous because they come from various sources (scientific bibliography, industrial data, etc); data may be imprecise because of the complexity of the underlying biological processes that are involved. To deal with heterogeneity, MIEL queries the database through several views simultaneously. To query incomplete data, MIEL proposes to use a fuzzy set, expressing the query preferences of the user. Fuzzy sets may be defined on a hierarchized domain of values, called an ontology (values of the domain are connected using the a kind of semantic link). MIEL also proposes two optional functionalities to help the user query the database: i) MIEL can use the ontology to enlarge the querying in order to retrieve the nearest data corresponding to the selection criteria; and ii) MIEL proposes fuzzy completion rules to help the user formulate his/her query. To query imprecise data stored in the database with fuzzy selection criteria, MIEL uses fuzzy pattern matching.