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I am trying to use Gensim LDA modelling to topic model of dataset of food recipes. I wish to have topics based the key ingredients in the recipe. But the recipe text contains more words that are generic English and are not ingredient names. Hence my topic outcome is not as good as expected. I am trying to understand the impact of word frequency in the LDA topic outcome. Thanks.

Sid
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Have you tried removing stop-words from the data on which you construct LDA model?

Also, please bear in mind that it is not really possible to influence the assignment of words among the topics. This has been discussed in the answer to this question: how to improve word assignement in different topics in lda

sophros
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