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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Considering that words with different characteristic in the text havedifferent importance for classification, grouping them together separately canstrengthen the semantic expression of each part. Thus we propose a new textrepresentation scheme by clustering words according to their latent semanticsand composing them together to get a set of cluster vectors, which are thenconcatenated as the final text representation. Evaluation on fiveclassification benchmarks proves the effectiveness of our method. We furtherconduct visualization analysis showing statistical clustering results andverifying the validity of our motivation.

Mimicking Human Process: Text Representation via Latent Semantic Clustering for Classification