Identifying patterns in text using topic modeling
The topic modeling
refers to the process of identifying hidden patterns in text data. The goal is to uncover some hidden thematic structure in a collection of documents. This will help us in organizing our documents in a better way so that we can use them for analysis. This is an active area of research in NLP. You can learn more about it at http://www.cs.columbia.edu/~blei/topicmodeling.html. We will use a library called gensim during this recipe. Make sure that you install this before you proceed. The installation steps are given at https://radimrehurek.com/gensim/install.html.
How to do it…
- Create a new Python file and import the following packages:
from nltk.tokenize import RegexpTokenizer from ...
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