Bag of Words (BoW)

The Bag of Words model is a fundamental method for text representation. It converts text into a vector of word frequencies, disregarding grammar and word order.

• Vocabulary Creation:
  • A vocabulary of all unique words in the text corpus is created.
• Frequency Vector:
  • Each document is represented as a vector indicating the frequency of each word in the vocabulary.
• Example:
  • Corpus: ["I love data science", "data science is amazing"]
  • Vocabulary: ["I", "love", "data", "science", "is", "amazing"]
  • Frequency Vectors:
    • Document 1: [1, 1, 1, 1, 0, 0]
    • Document 2: [0, 0, 1, 1, 1, 1]