MOSIG Master 2ND YEAR Research
YEAR 2011/2012

ADVISOR: Jérôme David and Jérôme Euzenat

TEL: +33 (0)476 61 53 66

EMAIL: Jerome:David#inria:fr, Jerome:Euzenat#inria:fr

TEAM AND LAB: Exmo team, INRIA & LIG

MASTER PROFILE: Artificial intelligence and the web

Reference number: Proposal n°1044

TITLE:

The goal of the semantic web is to take advantage of formalised knowledge (in languages like RDF) at the scale of the worldwide web. In particular, it is based on ontologies which define concepts used for representing knowledge on the web, e.g., for annotating a picture, specifying a web service interface or expressing the relation between two persons. However, it is likely that different information sources and different actors in different contexts will use different ontologies. It is thus necessary to find correspondences between concepts of these ontologies.

The operation of finding correspondences is called ontology matching [1]. It takes two ontologies as input and outputs a set of correspondences between entities of these ontologies. A correspondence is defined by the two related entities, which can be classes, instances, properties, formulas as well as combination of those, the relation between these entities (equivalence, subsumption, incompatibility, etc.) and, if possible, a confidence measure in this correspondence. Alignments are used for importing data from one ontology to another or for translating queries.

Mathieu d'Aquin recently proposed measures for assessing agreement and disagreement between ontologies [2,3]. These measures are mostly based on the compatibility or redundancy of one ontology assertions in the other ontology. Even if this is hidden in the initial formulation, these measures also rely on an alignment between the ontologies. They are very interesting because they assess the relation between two ontologies through an alignment without external reference: usually we evaluate alignment correctness with the help of a reference alignment [4].

We propose to reconsider these measures in order to provide two improvements to them:

• reintroducing alignments at the core of the measures;
• replacing the currently syntactic compatibility comparison by more semantic ones, e.g., entailment and consistency.

Finally, because they are independent from the reference, such measures may be used as alignment improvers: it may be possible to optimise existing alignments by attempting at maximising ontology aggreement and/or minimising ontology disagreement. We propose to experiment with this idea and to apply it either to randomly generated alignments or to alignments returned by existing alignment evaluation campaigns [6] in order to determine if it indeed provides improvement for matchers.

Expected results

• Redefinition of agreement and disagreement measures that is more general than those available;
• Experimentation with these measures as alignment improvers;
• Implementation of these measures and the alignment improver within the Alignment API [7,8];

Références

[1] Jérôme Euzenat, Pavel Shvaiko, Ontology matching, Springer, Berlin (DE), 2007
[2] Mathieu d'Aquin, Formally measuring agreement and disagreement in ontologies, Proc. 5th International Conference on Knowledge Capture (K-Cap), Redondo Beach (CA US), pp145-152, 2009 http://watson.kmi.open.ac.uk/DownloadsAndPublications_files/kcap09.pdf
[3] Mathieu d'Aquin, Enrico Motta, Visualizing consensus with online ontologies to support quality in ontology development. Proc. EKAW workshop on Ontology Quality (OntoQual), 2010.http://watson.kmi.open.ac.uk/DownloadsAndPublications_files/ontoqual2010.pdf
[4] Jérôme Euzenat, Christian Meilicke, Pavel Shvaiko, Heiner Stuckenschmidt, Cássia Trojahn dos Santos, Ontology alignment evaluation initiative: six years of experience, Journal on Data Semantics XV:158-192, 2011 http://disi.unitn.it/~p2p/RelatedWork/Matching/OAEI-JODS.pdf
[5] Christian Meilicke, Heiner Stuckenschmidt, Incoherence as a basis for measuring the quality of ontology mappings, Proc. 3rd International Workshop on Ontology matching (OM), Karlsruhe (DE), pages 1-12, 2008 http://disi.unitn.it/~p2p/OM-2008/om2008_Tpaper1.pdf
[6] http://oaei.ontologymatching.org
[7] Jérôme David, Jérôme Euzenat, François Scharffe, Cássia Trojahn, The Alignment API 4.0, The semantic web journal 2(1):3-10, 2011 http://www.semantic-web-journal.net/sites/default/files/swj60_1.pdf
[8] http://alignapi.gforge.inria.fr

MOSIG Master 2E ANNÉE Research
ANNÉE 2011/2012

RESPONSABLES: Jérôme Euzenat and Jérôme David

TÉL: +33 (0)476 61 53 66

ADRESSE ÉLECTRONIQUE: Jerome:Euzenat#inrialpes:fr, Jerome:David#inria:fr

LABORATOIRE ET ÉQUIPE: Équipe Exmo, INRIA & LIG

PROFIL DU PROJET: Parcours web et intelligence artificielle

TITRE: