Before you begin training the model, it is crucial to understand and outline the objectives you are trying to achieve by using Re:infer. It is likely that you will have more than one, and you should think about how these would best align to how you then create taxonomies on your datasets.

 

You may be able to meet several objectives with one taxonomy, but remember, you can always create a separate taxonomy on a copy of the same dataset in future, to suit another objective. Just remember, taxonomies need to be suitable for the data sources to which they are applied.

 

It’s best not to try and achieve absolutely everything at once within one taxonomy, as this can become very difficult to train and maintain. It is much easier to start with a limited taxonomy for a specific purpose. For example, analysing in-app customer feedback data for product feature requests and product bugs, or monitoring client servicing with a view to improving it.



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