Bag of Words Model

A bag of words model is essentially counting words per document.


Data Structure

Rows are documents and columns are words or phrases. Inevitably this is a sparse matrix.


Implementation

First the words and phrases across all documents must be tokenized.

Next, the count of each key word/phase is extracted from each document.

Finally, the output matrix must be interpreted. Semantic meaning is lost so care must be taken to ensure that sourced documents have a common context.


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Statistics/BagOfWordsModel (last edited 2025-01-10 16:19:13 by DominicRicottone)