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Optimizing Ontology Alignments by Using Genetic Algorithms Jorge Martinez-Gil, Enrique Alba, and Jos´e F.
This work is about an experiment in which we have compared the textual rendering of ontologies in order to get more accurate alignments between them.
The reason is that obtaining satisfactory ontology alignments is a key aspect for such ﬁelds as:
However, there are still some problem areas to be solved, because experts are still needed to supervise the matching processes and an efficient way to reuse the alignments has not yet been found.
Photographic Survey Conducted by D.M.Irving 13/5/2015 Greyabbey Bay, Bootown MRD149:012 Stone Alignments Description On File This feature is situated at a distance of over 200m from the shoreline in a relatively flat area of silty sand.
As one might expect, the 1 number of alignments increases exponentially with the size of the networks, so checking the score of every possible alignment is impractical.
The second approach is called genetics for ontology alignments and is based on a genetic algorithm which scales better for a large number of atomic matching algorithms in the composite algorithm and is able to optimize the results of the matching process (Martinez-Gil &
On the other hand, functions for calculating alignments can be divided into similarity measures and distance measures.