I'm trying to evaluate a home-made topic model. For this, I'm using the list of topics (represented by keywords), and want to use a gensim.models.coherencemodel.CoherenceModel
, and call it on a corpus, which is a list of strings (each one being a document). The CoherenceModel
requires a Dictionary
, but I don't understand what this corresponds to, and how I can get it. I'm using the TfidfVectorizer
from sklearn
to vectorize the text, and glove
embeddings from gensim
to compute similarities within my model.
From the docs, a Dictionary
can be created from a corpus where the corpus is a list of lists of str
. This same corpus should be passed in the text
argument of the CoherenceModel
.
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