As Im diving into topic modeling, I dont understand the process concerning learning corpus and the individual corpus of the documents you want to work with.
Are they the same corpus? No right?
So do you train the model on Wikipedia e.g., get topics and document distributions of wikipedia & later apply it on your book collection about whatever to find their topics?
As you preprocess the data, do you preprocess both corpus if they are not the same?
Do you evaluate the wikipedia learned model or the model/ topics of your individual corpus of books?
Thank you in advance!
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