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

Nowadays, micro blog has been widely used as a platform of information sharing. How to help users to find what they are interested in from massive amount of data becomes a very challenging issue. Some micro blog recommend systems are user-based and its effect is not significant. In this paper, we implement the recommendation system based on micro blog, users can subscribe the post which they are interested in, and system will recommend the related posts to users combined with user interest. This paper cluster users by their interest and experimental results show that the improved K-Means clustering algorithm can achieve a better accuracy and running time and our algorithm is more effective than traditional algorithm.

A Micro blog Recommendation System Based on User Clustering