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

The classification problem has got a new importance dimension with the growing aggregated value which has  been given to the Social Media such as Twitter. The huge number of small documents to be organized into  subjects is challenging the previous resources and techniques that have been using so far. Futhermore, today  more than ever, personalization is the most important feature that a system needs to exhibit. The goal of many  online systems, which are available in many areas, is to address the needs or desires of each individual user. To  achieve this goal, these systems need to be more flexible and faster in order to adapt to the userâs needs. In this  work, we explore a variety of techniques with the aim of better classify a large Twitter data set accordingly to a  user goal. We propose a methodology where we cascade an unsupervised following by supervised technique.  For the unsupervised technique we use standard clustering algorithms, and for the supervised technique we  propose the use of a kNN algorithm and a Centroid Based Classifier to perform the experiments. The results  are promising because we reduced the amount of work to be done by the specialists and, in addition, we were  able to mimic the human assessment decisions 0.7907 of the time, according to the F1-measure.

Combining Clustering and Classification Approaches for Reducing the Effort of Automatic Tweets Classification