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| ## page was renamed from NaturalLanguageProcessing/BagOfWords = Bag of Words = |
= Bag of Words Model = |
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| A '''bag of words''' model is essentially counting words per document. | A '''bag of words model''' is essentially counting words per document. |
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| Finally, the output matrix must be interpretted. Semantic meaning is lost so care must be taken to ensure that sourced documents have a common context. | 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. |
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.