Overview of YAM++-(not) Yet Another Matcher for ontology alignment task
Résumé
Several challenges to the field of ontology matching have been outlined in recent research. The selection of
the appropriate similarity measures as well as the configuration tuning of their combination are known as
fundamental issues the community should deal with. Verifying the semantic coherence of the discovered
alignment is also known as a crucial task. As the challenging issues are both in basic matching techniques
and in their combination, our approach is aimed to provide improvement at the basic matcher level and
also at the level of framework. Matching large scale ontologies is currently one of the most challenging
issues in ontology matching field. The main reason is that large ontologies are highly heterogeneous both
at terminological and conceptual levels. Furthermore, matching very large ontologies entails exploring
a very large searching space to discover correspondences. It may also require a huge amount of main
memory to maintain the temporary results at each computational step. These factors strongly impact the
effectiveness and efficiency of any ontology matching tool. To overcome these issues, we have developed
a disk-based ontology matching approach. The underlying idea of our approach is that the complexity
and therefore the cost of the matching algorithms are reduced thanks to the indexing data structures by
avoiding exhaustive pair-wise comparisons. Indeed, we extensively used indexing techniques in many
places. For example, we defined a bitmap encoding the structural information of an ontology. This
indexing structure will be exploited for accelerating similarity propagation. Moreover, our approach uses
a disk-based mechanism to store temporary data. This allows to perform any ontology matching task
on a simple PC or laptop instead of a powerful server. In this paper, we describe YAM++, an ontology
matching tool, aimed at solving these issues. We evaluated the efficiency of YAM++ in various OAEI 2012
and OAEI 2013 tracks. YAM++ was one of the best ontology matching systems in terms of F-measure. Most
notably, the current version of YAM++ has passed all scalability and large scale ontology matching tests
and obtained high matching quality results.
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