Vector Space Model


Contents:

  1. Bag-of-words matching
  2. Overview of the vector space model
  3. Query and document vectors
  4. Dot product and Euclidean distance
  5. Term weighting
  6. Inverse document frequency (idf)
  7. Feature selection with tf-idf
  8. Document length normalization
  9. State-of-the-art retrieval formula
  10. tf-idf weighted sum
  11. Cosine and Jacquard coefficient
  12. Cosine with tf-idf weights
  13. p-norm and chi-squared distance
  14. Phrases and multi-word features
  15. Applications of the VSM