This workflow is part of a number of other workflows that address a data mining scenario at the intersection of active learning, text mining, stream mining and service-oriented knowledge discovery architectures. This workflow, in particular, provides a graphical interface on the Webportal for a KNIME specialist to re-label the question with the most uncertain predicted classes. It starts by first reading a subset of the training set (10% of the most uncertain predicted classes). Then, it loops over all the questions, and for each one those, it allows the specialist to choose between one of the predicted classes or the option "Something Else". The labeling phase takes place in the "Choose Answer" webpage. To complete the execution of the loop the specialist has to complete the labeling for all the no-processed questions of the subset of the training set, or to click "Exit". If the specialist clicks "Exit" the workflow saves the last step of the loop iteration. Thus, when the specialist starts again the execution of the workflow on the WebPortal, he/she will be able to start labeling the questions from the last loop iteration. After the Variable Condition Loop End the data get split between questions that have been classified as "Something Else" and all the other categories. These two datasets are then saved into two different tables.
This is a companion discussion topic for the original entry at https://kni.me/w/tknOeJ8wh0eoxNa7