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Since the MeSH subpart with one-word rubrics is produced through filtering, correlation is not a relevant measure.
The other two types of static resources are a parts-of-speech blocker and the MeSH-dictionary created from one-word rubrics in MeSH.
This partition, together with partition 5, also has the highest number of unique words per rubric.
However, this partition is from one single chapter of NCSP and compared to the other partitions it has an extremely low number of unique words per rubric.
The many repetitions of the same words in the rubrics gives many possibilities to discover the correspondences of the words when the resources are generated and this is the most probable reason for the good results.
Instead we analysed the ratio between the numbers of words in corresponding rubrics.
In the rubric ratio analysis we calculated the grand mean (q ¯ ) of the number of words in the English rubrics (e ) and the number of words in the corresponding Swedish rubrics (s ) for all rubrics (n ).
Because of the repetitive structure of terminology system rubrics, the word alignment differences were also repetitive.
This means that for each word in a Swedish rubric 1.29 words can be expected in the corresponding English rubric.
The measured similarities and differences were mainly based on whether the used words (contents) in the rubrics were the same, whether the structures of the rubrics were repetitive and whether the structures in the translations were changed according to the original.
We started the experiments with preparation and the author MN manually word aligned the terminology system rubrics in the training set.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com