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Bag-of-Words Model

[bæɡ əv wɜrdz ˈmɑdəl]
Natural Language Processing
Last updated: December 9, 2024

Definition

A simplified text representation that counts word occurrences while ignoring grammar and word order.

Detailed Explanation

The Bag-of-Words model creates a vocabulary from all unique words in a document collection and represents each document as a vector of word frequencies. While simple, it loses word order information and context but remains useful for many applications.

Use Cases

Document classification, spam detection, topic modeling, sentiment analysis

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