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bag-of-words

A sparse vector of raw word counts over a fixed vocabulary, with word order thrown away entirely.

A bag-of-words representation counts how many times each vocabulary word appears in a document and stores those counts as a vector, one dimension per vocabulary word. It discards word order completely -- "dog bites man" and "man bites dog" produce the identical vector -- which is exactly what limits how much meaning a bag-of-words representation can capture.

Examples

  • The sentences "the dog bit the man" and "the man bit the dog" produce the identical bag-of-words vector: {the: 2, dog: 1, bit: 1, man: 1}.

See also

TF-IDF
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