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

I propose a novel dual-attention model(DAM) for aspect-level sentimentclassification. Many methods have been proposed, such as support vectormachines for artificial design features, long short-term memory networks basedon attention mechanisms, and graph neural networks based on dependency parsing.While these methods all have decent performance, I think they all miss oneimportant piece of syntactic information: dependency labels. Based on thisidea, this paper proposes a model using dependency labels for the attentionmechanism to do this task. We evaluate the proposed approach on three datasets:laptop and restaurant are from SemEval 2014, and the last one is a twitterdataset. Experimental results show that the dual attention model has goodperformance on all three datasets.

Dual-Attention Model for Aspect-Level Sentiment Classification