Database Reference
In-Depth Information
CONCLUSION
Buche, P., Dervin, C., Haemmerlé, O., & Thomo-
poulos, R. (2005). Fuzzy querying of incomplete,
imprecise, and heterogeneously structured data in
the relational model using ontologies and rules.
IEEE transactions on Fuzzy Systems
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13
(3),
373-383. doi:10.1109/TFUZZ.2004.841736
In this chapter, we have presented an ontology-
based data integration system in the field of food
safety. This system allows data of different nature
(contamination data and consumption data) and of
different sources (filled manually, coming from
existing databases or extracted from the Web) to
feed together a decision support system to compute
the exposure of a given population of consumers
to chemical contaminants.
The essential point to retain from this chapter
is that the ontology is the core of our data inte-
gration system. We have proposed three original
processes to integrate data according to a domain
ontology. First, the semantic annotation process
proposes an unsupervised aggregation approach
from cells to relations to annotate Web data tables
according to a domain ontology. Second, the que-
rying process relies on a flexible querying system
which takes into account the pertinence degrees
generated by the semantic annotation process.
Third, the ontology alignment process proposes
to find correspondences between objects of a
source ontology and objects of a target ontology
by means of rules which exploit the characteristics
and their values associated with each objects of
both ontologies.
Buche, P., Dibie-Barthélemy, J., & Ibanescu, L.
(2008). Ontology Mapping using fuzzy conceptual
graphs and rules. In P. Eklund & O. Haemmerlé
(Eds.),
Supplementary Proceedings of the 16
th
International Conference on Conceptual Struc-
tures
(pp. 17-24).
Buche, P., Soler, L., & Tressou, J. (2006). Le
logiciel CARAT. In P. Bertail, M. Feinberg, J. Tres-
sou. & P. Verger (Eds.),
Analyse des risques ali-
mentaires
(pp. 305-333). Lavoisier Tech&Doc.
Campi, A., Damiani, E., Guinea, S., Marrara, S.,
Pasi, G., & Spoletini, P. (2006). A fuzzy extension
for the Xpath query language. In
Flexible Query
Answering Systems
(LNCS 4027, pp. 210-221).
Berlin, Germany: Springer.
Castano, S., Ferrara, A., Montanelli, S., Hess, G.
N., & Bruno, S. (2007).
BOEMIE (bootstrapping
ontology evolution with multimedia information
extraction). State of the art on ontology coordina-
tion and matching
(FP6-027538 Delivrable 4.4).
Università degli Studi di Milano.
Corby, O., Dieng-Kuntz, R., & Faron-Zucker, C.
(2004). Querying the Semantic Web with corese
search engine. In
Proceedings of the 16
th
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Conference on Artificial Intelligence. Subconfer-
ence PAIS'2004
(pp. 705-709). Amsterdam: IOS
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