Advances in Ontology Matching

Abstract

Matching of concepts describing the meaning of data in heterogeneous distributed information sources, such as database schemas and other metadata models, grouped here under the heading of an ontology, is one of the basic operations of semantic heterogeneity reconciliation. The aim of this chapter is to motivate the need for ontology matching, introduce the basics of ontology matching, and then discuss several promising themes in the area as reflected in recent research works. In particular, we focus on such themes as uncertainty in ontology matching, matching ensembles, and matcher self-tuning. Finally, we outline some important directions for future research.

Tuning the ensemble selection process of schema matchers

“…Similarity matrices are generated by schema matchers. Schema matchers are instantiations of the schema matching process [26,49]. They differ mainly in the measures of similarity they employ, yielding different similarity matrices.…”

Agent-mediated shared conceptualizations in tagging services

“…In a more general framework, and due to the popularity of tagging as weak knowledge organization method, it is worthwhile to emphasize how useful the Knowledge reconciliation method presented in the paper is for the automatization of integration of distributed information sources. The ambiguity in concept interpretation, also known as semantic heterogeneity, has become one of the main obstacles to this process [9]. Since our method is based on FCA, reconciliation is a disambiguation of concept interpretation between two users.…”

Ontology Mapping for Enhanced Interoperability of S-100 Geographic Information Registers

“…It becomes necessary for multiple ontologies to be accessed from several applications. Multiple ontologies representing various levels of meaning and/or different domains can provide information on complicated tasks [6][7][8][9][10][11].…”

“…Much research on ontology-mapping methods and tools such as ontological signature morphism, ontology alignment, ontology morphism, word translation and integration, and others, have been introduced. These can be classified into categories, such as frameworks, methods, translators, and mediators [6][7][8][9][10][11].…”