I am selecting manually several hundreds Google Alerts (GA) texts those that are indeed relevant for my research vs those which are not (despite they are all triggered by some relevant search keywords).
Basically each week I get several hundreds GA email such as:
From such emails I create a file such as:
This is really becoming a time consuming procedure, hence my decision to try applying artificial intelligence solutions to such a case.
What sort of supervised learning algorithm would you advise that I adopt so that it can learn by example from my choices and decide on my behalf whether to retain the piece of information or not - see Retain=Yes/No in the attached file. That is: I can classify a few hundreds cases and then let the algorithm learn and classify future/additional data. I plan to regularly review such a classification, correct missclassifications and train the algorithm again with the objective to improve its ability to correctly classify the GA texts according to the examples I provide the algorithm.
I am also looking for solutions in software. My preferred software is R, but I am also open to other software.