The recommendation API finds nearest neighbors on a multi-dimensional data mesh. On the one hand, you
can add data to your mesh (e.g. by sending usage data of your website). On the other hand, you can request
the nearest neighbor for a certain data profile (e.g. to recommend sub-pages to a user).
All you have to do is to call the danubeRecommendation method of your DanubeClient instance with your data. With each request, the correlation matrix
of your data history is refined and better recommendations are returned.
You can call the resetCorrelationMatrix method of your DanubeClient instance to reset the current correlation matrix of your API key.Note that this is a powerful operation as your whole data history will be deleted! If you should accidentally reset your correlation matrix you
can contact us and we will try to help.