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

An important chain of supermarkets in the western zone of thecapital of Chile, needs to obtain key information to make decisions, thisinformation is available in the databases but needs to be processed due to thecomplexity and quantity of information which becomes difficult to visualiz,.Method: For this purpose, an algorithm was developed using artificial neuralnetworks applying Kohonen's SOM method. To carry it out, certain key proceduresmust be followed to develop it, such as data mining that will be responsiblefor filtering and then use only the relevant data for market basket analysis.After filtering the information, the data must be prepared. After datapreparation, we prepared the Python programming environment to adapt it to thesample data, then proceed to train the SOM with its parameters set after testresults. Result: the result of the SOM obtains the relationship between theproducts that were most purchased by positioning them topologically close, toform promotions, packs and bundles for the retail manager to take intoconsideration, because these relationships were obtained as a result of the SOMtraining with the real transactions of the clients. Conclusion: Based on this,recommendations on frequent shopping baskets have been made to the supermarketchain that provided the data used in the research

An\'alisis de Canasta de mercado en supermercados mediante mapas auto-organizados