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A common approach for this is LDA (Latent Dirichlet Allocation), which not only gives you the groups, but also a way to identify the topics of the groups by giving you the most common or distinctive words for each topic.


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I did something similar a while ago. We wanted to classify several types of pdf. We first extracted the text of the documents. We created NLP features with the text Then added pdf metadata: size of the file, number of pages, name of the document... We then built a classification model with a few samples and did Active Learning I guess that you could also ...


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The big problem with docx files is that they have a ton of content related to formatting that most people find irreverent when scraping docx files. Hence, one approach is to convert the docx files to something more friendly like json that excludes all the irrelevant bits, and then use existing frameworks like JSON schema for pattern matching and jmespath ...


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