The bag-of-words model is a simplified way to represent text data in which the text is treated as a collection of words, disregarding grammar and word order but keeping track of the frequency of each word. This approach allows for the conversion of text into a numerical format that can be easily processed by machine learning algorithms, making it an essential technique in text preprocessing and feature extraction.
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