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Symbol not found
Hello @sekhansen ,
I am trying to play around with your tutorial.
After following all the installation (I am on Mac) , I try to run the code from :
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Python 2.7 and the tutorial.py, I got :
Traceback (most recent call last): File "/Users/rbellebon/text-mining-tutorial/tutorial.py", line 9, in <module> import topicmodels File "/Users/rbellebon/text-mining-tutorial/topicmodels/__init__.py", line 5, in <module> from . import LDA File "/Users/rbellebon/text-mining-tutorial/topicmodels/LDA/__init__.py", line 2, in <module> from .gibbs import * File "/Users/rbellebon/text-mining-tutorial/topicmodels/LDA/gibbs.py", line 17, in <module> from topicmodels.samplers import samplers_lda ImportError: dlopen(/Users/rbellebon/text-mining-tutorial/topicmodels/samplers/samplers_lda.so, 2): Symbol not found: _gsl_rng_mt19937 Referenced from: /Users/rbellebon/text-mining-tutorial/topicmodels/samplers/samplers_lda.so Expected in: flat namespace
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Python 3.6 and junyper notebook, when I execute import topicmodels, I got:
ImportError: dlopen(/Users/rbellebon/text-mining-tutorial/topicmodels/samplers/samplers_lda.so, 2): Symbol not found: _PyClass_Type Referenced from: /Users/rbellebon/text-mining-tutorial/topicmodels/samplers/samplers_lda.so Expected in: flat namespace in /Users/rbellebon/text-mining-tutorial/topicmodels/samplers/samplers_lda.so
Any idea on what can be wrong?
Thanks in advance,
Less harsh handling of non utf-8 text
German text messages - stop words and stemming
Hi @sekhansen,
Thanks a lot for the tutorial! I like it in a lot and I trief to apply it to my own work.
However, unfortunately, I would like to analyze German text messages.
Is there a way to additionally implement a German stop word list to the "short" and "long" English list?
stopwords_german.txt
And what about the stemming? I just noticed that there is a German package in the NLTK package, but I do not know how to apply it.
I think the rest of the code is not a problem re language :-)
I am really a freshman at this topic, so every help is really appeciated.
Thanks in advance!
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