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

Words and character-bigrams are both used as features in Chinese text processing tasks, but no systematic comparison or analysis of their values as features for Chinese text categorization has been reported heretofore. We carry out here a full performance comparison between them by experiments on various document collections (including a manually word-segmented corpus as a golden standard), and a semi-quantitative analysis to elucidate the characteristics of their behavior; and try to provide some preliminary clue for feature term choice (in most cases, character-bigrams are better than words) and dimensionality setting in text categorization systems.

A comparison and semi-quantitative analysis of words and character-bigrams as features in Chinese text categorization