18 résultats avec le mot-clé: 'sema results ontology alignment contest oaei'
SEMA combines lexical, semantic and structural matching algorithms: A semantic matching method exploiting Latent Dirichlet Allocation model (LDA) [3], requiring no
N/A
(2) The similarity propagation strategy could compensate for the linguistic matching methods, and it can produce more alignments when ontologies lack of linguistic
N/A
To solve the matching problem without rich literal information, a similarity propagation matcher with strong propagation condition (SSP matcher) is presented, and the
N/A
Thus if the given ontology does not contain the name of the ontological concepts and properties, the OntoDNA is not able to discover lexical similarity for resolving the
N/A
To solve the matching problem without rich literal information, a similarity propagation matcher with strong propagation condition (SSP matcher) is presented, and the
N/A
In The 4th International Workshop on Ontology Matching, Washington Dc., USA (2009) [2] Peng Wang, Baowen Xu: Lily: Ontology Alignment Results for OAEI 2008.
N/A
In The 4th International Workshop on Ontology Matching, Washington Dc., USA (2009) [2] Peng Wang, Baowen Xu: Lily: Ontology Alignment Results for OAEI 2008.
N/A
This paper presents and discusses the results produced by the alignment systems MapPSO and MapEVO for the 2011 Ontology Alignment Evaluation Initiative (OAEI).. The two
N/A
Ainsi depuis 1993, 41 jeunes gypaètes barbus (23 femelles, 18 mâles) ont été réintroduits dans les Alpes du sud au sein de deux parcs (Parc national du Mercantour et
N/A
The EON Ontology Alignment Contest attempts to overcome these problems in inviting tool developers to perform a series of experiments in ontology alignment and compare their results
N/A
The ultimate goal is to incorporate methods that exploit different types of infor- mation available (lexical, semantic, structural) at various settings
N/A
It performs an oriented alignment (from a source to a target ontology) and takes into account labels and sub-class descriptions.. Our participation in last year edition of
N/A
Moreover, our mapping techniques are strict: only concepts that have strictly the same label are matched with an equivalence relation.. The remaining concepts of the source ontology
N/A
As only equivalence relationships will be evaluated in the alignment contest, we did not use this year the techniques which generate isA relationship (except in the Task 3) and
N/A
It performs an oriented alignment (from a source to a target ontology) and takes into account labels and sub-class descriptions.. Our participation in last year edition of
N/A
A novel Ontology Alignment Evaluation Initiative (OAEI) track, Ontology Alignment for Query Answering (OA4QA), introduced in the 2014 evaluation cam- paign, aims at bridging this gap
N/A
We present a hybrid alignment strategy for anatomical entities, combining direct and indirect alignment techniques, both supported by the NLM Anatomy Ontology Alignment System
N/A