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

A set of ontology matching algorithms (for finding correspondences betweenconcepts) is based on a thesaurus that provides the source data for thesemantic distance calculations. In this wiki era, new resources may spring upand improve this kind of semantic search. In the paper a solution of this taskbased on Russian Wiktionary is compared to WordNet based algorithms. Metricsare estimated using the test collection, containing 353 English word pairs witha relatedness score assigned by human evaluators. The experiment shows that theproposed method is capable in principle of calculating a semantic distancebetween pair of words in any language presented in Russian Wiktionary. Thecalculation of Wiktionary based metric had required the development of theopen-source Wiktionary parser software.

Related terms search based on WordNet / Wiktionary and its application in Ontology Matching