RiMOM results for OAEI 2008

For Instance Matching, our main idea is that we classify individuals by their classes, complete information of each individual as complete as possible, run matching algorithm for

Then we give new features in instance matching compared with traditional ontology matching (schema matching) and introduce the specific techniques we used for the 3 different

Our algorithm contains preprocess- ing, adaptation module for OAEI 2008, the basic block of algorihtm and the local align- ment process.. We created our own persistent model

The second stage of AROMA discovers the subsumption relations by using the association rule model and the implication intensity measure [Gras et al., 2008]. an implication allowing

The Automated Semantic Mapping of Ontologies with Validation (ASMOV) algorithm for ontology alignment was one of the top performing algorithms in the 2007

In the context of ontology matching, the class of compound nouns semantic relation detection algorithms may be used in order to determine such relations within ontology

GeRoMeSuite is based on the generic role based meta- model GeRoMe [3], which represents models from different modeling languages (such as XML Schema, OWL, SQL) in a generic

Similarity Aggregation: For each instance pair, after acquiring similarity values in terms of multiple aligned predicates, we need to aggregate the similarities to get fi- nal