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

We present a language independent, unsupervised method for building wordembeddings using morphological expansion of text. Our model handles the problemof data sparsity and yields improved word embeddings by relying on trainingword embeddings on artificially generated sentences. We evaluate our methodusing small sized training sets on eleven test sets for the word similaritytask across seven languages. Further, for English, we evaluated the impacts ofour approach using a large training set on three standard test sets. Our methodimproved results across all languages.

Unsupervised Morphological Expansion of Small Datasets for Improving Word Embeddings