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The bag-of-words model is a simplified representation used in natural language processing and text mining where text is treated as an unordered collection of words, disregarding grammar and word order but keeping track of word frequency. This model enables efficient text analysis and helps in various applications like sentiment analysis by transforming text into a numerical format that can be easily processed by algorithms.
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