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machine learning - Topic Modeling Corpus

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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