Nov-20-2018, 04:56 PM
Hi guys,
I have a question about Topic Modeeling with NLTK & Gensim.
I just started to deal with this topic and the Python language. Nevertheless, I could achieve a satisfactory result with the linked "guide", but I would like to extend it.
Topic Modelling in Python with NLTK and Gensim
Now to my question:
I processed my test dataset with the code as in the linked guide and had it visualized afterwards. Here I could also find the previously known topics of the documents.
Now I would like to have the individual documents labeled accordingly.
My data set is available as a .csv file which contains the documents as a simple list. Now the identified topics are to be written simply behind the individual documents.
Is there perhaps an integrated function for this or how can I solve this as simply as possible?
Kind regards
Nic
I have a question about Topic Modeeling with NLTK & Gensim.
I just started to deal with this topic and the Python language. Nevertheless, I could achieve a satisfactory result with the linked "guide", but I would like to extend it.
Topic Modelling in Python with NLTK and Gensim
Now to my question:
I processed my test dataset with the code as in the linked guide and had it visualized afterwards. Here I could also find the previously known topics of the documents.
Now I would like to have the individual documents labeled accordingly.
My data set is available as a .csv file which contains the documents as a simple list. Now the identified topics are to be written simply behind the individual documents.
Is there perhaps an integrated function for this or how can I solve this as simply as possible?
Kind regards
Nic