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

Cross-Language Information Retrieval (CLIR) and machine translation (MT)resources, such as dictionaries and parallel corpora, are scarce and hard tocome by for special domains. Besides, these resources are just limited to a fewlanguages, such as English, French, and Spanish and so on. So, obtainingcomparable corpora automatically for such domains could be an answer to thisproblem effectively. Comparable corpora, that the subcorpora are nottranslations of each other, can be easily obtained from web. Therefore,building and using comparable corpora is often a more feasible option inmultilingual information processing. Comparability metrics is one of key issuesin the field of building and using comparable corpus. Currently, there is nowidely accepted definition or metrics method of corpus comparability. In fact,Different definitions or metrics methods of comparability might be given tosuit various tasks about natural language processing. A new comparability,namely, termhood-based metrics, oriented to the task of bilingual terminologyextraction, is proposed in this paper. In this method, words are ranked bytermhood not frequency, and then the cosine similarities, calculated based onthe ranking lists of word termhood, is used as comparability. Experimentsresults show that termhood-based metrics performs better than traditionalfrequency-based metrics.

Termhood-based Comparability Metrics of Comparable Corpus in Special Domain