https://link.springer.com/content/pdf/10.1007%2F978-1-4615-6103-3_15.pdf

Fuzzy Mathematical Programming

Ontologies are today a key part of every knowledge based system. They provide a source of shared and precisely defined terms, resulting in system interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that a domain can be conceptualized results in the creation of different ontologies with contradicting or overlapping parts. For this reason ontologies need to be brought into mutual agreement (aligned). One important method for ontology alignment is the comparison of class and property names of ontologies using string-distance metrics. Today quite a lot of such metrics exist in literature. But all of them have been initially developed for different applications and fields, resulting in poor performance when applied in this new domain. In the current paper we present a new string metric for the comparison of names which performs better on the process of ontology alignment as well as to many other field matching problems.

/pdf/a-string-metric-for-ontology-alignment-2nt707crly.pdf

H. Hamacher

Papers

Sensitivity analysis in fuzzy linear programming