The amount of research papers published nowadays related to ontology matching is
remarkable and we believe that reflects the growing interest of the research community …

Automated Semantic Matching of Ontologies with Verification (ASMOV) is a novel algorithm
that uses lexical and structural characteristics of two ontologies to iteratively calculate a …

In this paper, we propose a novel design for large-scale graph processing on FPGA. Our
design uses large external memory for storing massive graph data and FPGA for …

It has been a formidable task to achieve efficiency and scalability for the alignment between
two massive, conceptually similar ontologies. Here we assume, an ontology is typically …

In this work we present GOAL (Genetics for Ontology Alignments) a new approach to
compute the optimal ontology alignment function for a given ontology input set. Although this …

In this paper we propose an ontology matching paradigm based on the idea of harvesting
the Semantic Web, ie, automatically finding and exploring multiple and heterogeneous …

The Automated Semantic Mapping of Ontologies with Validation (ASMOV) algorithm for
ontology alignment has consistently been one of the top performing algorithms in the …

Nowadays many techniques and tools are available for addressing the ontology matching
problem, however, the complex nature of this problem causes existing solutions to be …

Ontology alignment is the key point to reach interoperability over ontologies. In semantic
web environment, ontologies are usually distributed and heterogeneous and thus it is …

While lots of research in ontology matching is related to the issue of computing and refining
similarity measures, only little attention has been paid to question how to extract the final …