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 propose a method to learn an individual model, which is to evaluate Japanese Compositions via Support Vector Regression, based on features along Japanese education and scores, marked by human in advance. We also propose a method to represent a way of evaluation. Features in training data of SVR are categorized as 7 types according to what each features refer to. The features include some features regarding criterions of Japanese compositions in education. Besides, all the features do not depend on topic of a composition’s prompt. Our methods implemented to score an integrated point of a composition automatically, and also to account elements considered by individual evaluator, to quantify weights of the each elements that contributes decision of scores.

Automated Evaluation of Japanese Compositions based on Features along Japanese Education and Construction of the Individual Evaluation Model