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 introduce the novel approach towards fake text reviews detection incollaborative filtering recommender systems. The existing algorithmsconcentrate on detecting the fake reviews, generated by language models andignore the texts, written by dishonest users, mostly for monetary gains. Wepropose the contrastive learning-based architecture, which utilizes the userdemographic characteristics, along with the text reviews, as the additionalevidence against fakes. This way, we are able to account for two differenttypes of fake reviews spamming and make the recommendation system more robustto biased reviews.

Mitigating Human and Computer Opinion Fraud via Contrastive Learning