Document-Feature Matrix

A Document-Feature Matrix (DFM) is a mathematical representation where rows are documents, columns are unique tokens (features), and cells contain frequency counts. It converts unstructured text into structured numerical format for computational analysis.

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Process

• Tokenization: Text is split into individual tokens (words)
• Vocabulary: All unique tokens form the matrix columns
• Counting: Each document-token pair is counted
• Sparse Matrix: Efficient storage format for large corpora

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Usage

The DFM is the foundation for all downstream analyses including keyword extraction, topic modeling, and semantic analysis. Create it after preprocessing (tokenization, stopword removal, lemmatization).

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