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

Discovering new trends and co-occurrences in massive data is a key step when analysing social media, data coming from sensors, etc. Although, nowadays Data Mining is very useful and widely used for the industry, business and government, the main problem of application of machine learning or data mining in other fields is the interpretability and complexity of obtained results for non-expert users in computer or data science. For this reason in the KDD process one of the most important phases is the interpretation and evaluation. In the case of association rules is essential that results are interpretable for experts. One of the most useful tools for this goal is the visualization, because it clarifies the interpretation of results, being easier to understand in order to take a decision or explaining the behaviour of data.

A comparative analysis of tools for visualizing association rules: A proposal for visualising fuzzy association rules