English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

To help developing a localization oriented EBMT system, an automatic machine translation evaluation method is implemented which adopts edit distance, cosine correlation and Dice coefficient as criteria. Experiment shows that the evaluation method distinguishes well between "good" translations and "bad" ones. To prove that the method is consistent with human evaluation, 6 MT systems are scored and compared. Theoretical analysis is made to validate the experimental results. Correlation coefficient and significance tests at 0.01 level are made to ensure the reliability of the results. Linear regression equations are calculated to map the automatic scoring results to human scorings.

An automatic evaluation method for localization oriented lexicalised EBMT system