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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper we present a new and simple language-independent method forword-alignment based on the use of external sources of bilingual informationsuch as machine translation systems. We show that the few parameters of thealigner can be trained on a very small corpus, which leads to resultscomparable to those obtained by the state-of-the-art tool GIZA++ in terms ofprecision. Regarding other metrics, such as alignment error rate or F-measure,the parametric aligner, when trained on a very small gold-standard (450 pairsof sentences), provides results comparable to those produced by GIZA++ whentrained on an in-domain corpus of around 10,000 pairs of sentences.Furthermore, the results obtained indicate that the training isdomain-independent, which enables the use of the trained aligner 'on the fly'on any new pair of sentences.

Using external sources of bilingual information for on-the-fly word alignment