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

A rapid growth of online advertisements results in unsolicited bulk of data being downloaded during web surfing. To tackle this problem a fast mechanism detecting adverts is required. In this paper we present the usefulness of URL based web-pages classification in the process of online advertisements detection. Our experiments are performed on seven popular classifiers using the real-life dataset obtained by human agents browsing the internet. We introduce a general and fully automated framework that allows us to do a comprehensive analysis by performing simultaneously hundreds of experiments. This study results in solution with 0.987 accuracy and 0.822 F-measure

An Automated Framework with Application to Study Url Based Online Advertisements Detection