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

Satisfaction measurement, which emerges in every sector today, is a veryimportant factor for many companies. In this study, it is aimed to reach thehighest accuracy rate with various machine learning algorithms by using thedata on Yemek Sepeti and variations of this data. The accuracy values of eachalgorithm were calculated together with the various natural language processingmethods used. While calculating these accuracy values, the parameters of thealgorithms used were tried to be optimized. The models trained in this study onlabeled data can be used on unlabeled data and can give companies an idea inmeasuring customer satisfaction. It was observed that 3 different naturallanguage processing methods applied resulted in approximately 5% accuracyincrease in most of the developed models.

Turkish Sentiment Analysis Using Machine Learning Methods: Application on Online Food Order Site Reviews