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

With the wild usage of deep learning in machine reading comprehension in the past few years,machine reading comprehension has developed rapidly.In order to improve machine reading comprehension’s semantic comprehension and inference abilities,an attention of bilinear function based Bi-LSTM model was proposed,which has good performance in extracting semantics of questions,candidates and articles,and producing the correct answers.We tested the model on CET-4and CET-6listening text materials.The results show that the accuracy rate of word-level input is about 2%higher than sentence-level input.Besides,the accuracy rate can increase about 8%after adding infe-rence structure with multi-layer attention.

基于双线性函数注意力Bi-LSTM模型的机器阅读理解 (Attention of Bilinear Function Based Bi-LSTM Model for Machine Reading Comprehension).