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How to build a Recommender System Slide 1 How to build a Recommender System Slide 2 How to build a Recommender System Slide 3 How to build a Recommender System Slide 4 How to build a Recommender System Slide 5 How to build a Recommender System Slide 6 How to build a Recommender System Slide 7 How to build a Recommender System Slide 8 How to build a Recommender System Slide 9 How to build a Recommender System Slide 10 How to build a Recommender System Slide 11 How to build a Recommender System Slide 12 How to build a Recommender System Slide 13 How to build a Recommender System Slide 14 How to build a Recommender System Slide 15 How to build a Recommender System Slide 16 How to build a Recommender System Slide 17 How to build a Recommender System Slide 18 How to build a Recommender System Slide 19 How to build a Recommender System Slide 20 How to build a Recommender System Slide 21 How to build a Recommender System Slide 22 How to build a Recommender System Slide 23 How to build a Recommender System Slide 24 How to build a Recommender System Slide 25 How to build a Recommender System Slide 26 How to build a Recommender System Slide 27 How to build a Recommender System Slide 28 How to build a Recommender System Slide 29 How to build a Recommender System Slide 30 How to build a Recommender System Slide 31 How to build a Recommender System Slide 32 How to build a Recommender System Slide 33 How to build a Recommender System Slide 34 How to build a Recommender System Slide 35 How to build a Recommender System Slide 36 How to build a Recommender System Slide 37 How to build a Recommender System Slide 38
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This presentation show the method to build a Recommender System with Collaborative FIltering method.

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How to build a Recommender System

  1. 1. Recommender System How to build a
  2. 2. Võ Duy Tuấn Technical Director @ dienmay.com  PHP 5 Zend Certified Engineer  Mobile App Developer  Web Developer & Designer  Interest: o PHP o Large System & Data Mining o Web Performance Optimization o Mobile Development
  3. 3. Introduction Collaborative Filtering Question & Answer AGENDA
  4. 4. 1. Introduction
  5. 5. APPLICATIONS • Personalized recommendation • Social recommendation • Item recommendation • Combination of 3 approaches above
  6. 6. AMAZON.COM | BOOKS
  7. 7. PLAY.GOOGLE.COM | APPS
  8. 8. SKILLSHARE.COM | CLASSES
  9. 9. PROCESS DIAGRAM Preprocessing Data Analysis Adjustment INPUT OUTPUT
  10. 10. TYPE OF RECOMMENDER SYSTEM • Collaborative filtering • Content-based filtering • Hybrid
  11. 11. 2. Collaborative Filtering
  12. 12. USER & ITEM
  13. 13. ORDER DATA
  14. 14. ORDER DATA (cont.)
  15. 15. ORDER DATA (cont.)
  16. 16. VECTOR & DIMENSION
  17. 17. VECTOR & DIMENSION
  18. 18. VECTORS
  19. 19. VECTORS
  20. 20. SIMILARITY CALCULATION
  21. 21. USER SIMILARITY MATRIX
  22. 22. SIMILARITY CALCULATION
  23. 23. SIMILARITY CALCULATION
  24. 24. SIMILARITY CALCULATION EXAMPLE
  25. 25. K-NEAREST-NEIGHBOR
  26. 26. K-NEAREST-NEIGHBOR
  27. 27. NEIGHBORS’ ORDER
  28. 28. REMOVE BOUGHT ITEMS
  29. 29. CALCULATING FINAL SCORE
  30. 30. OTHER SIMILARITY MEASURES More at: http://favi.com.vn/wp-content/uploads/2012/05/pg049_Similarity_Measures_for_Text_Document_Clustering.pdf
  31. 31. Problem ?!
  32. 32. COLLABORATIVE FILTERING PROBLEM • Fail with cold start problem o New User o New Item • Performance o Large Data set o Pre-calculate
  33. 33. PERFORMANCE EXAMPLE • We have 1,000,000 users (customers) • We sell 10,000 items - Total of similarity calculating = 1,000,000 x 1,000,000 = 1,000,000,000,000 - Each similarity calculate need 0.006s (on my MacBook Pro 2.2GHz Core i7, 8G Ram) => We need 1,000,000,000,000 x 0.006 = 6,000,000,000(s) ≈ 70,000 days ≈ 191 years - If store each similarity in 8 bytes, we need = 8,000,000,000,000 bytes ≈ 8,000 GB (on Memory or File)
  34. 34. ITEM-TO-ITEM COLLABORATIVE FILTERING (AMAZON.COM ) Download Paper: http://www.cs.umd.edu/~samir/498/Amazon-Recommendations.pdf
  35. 35. ADJUSTMENTS • Hybrid Recommender System • Sale forecast system • Context of User • Type of Item, Action • External (3rd-party) information.
  36. 36. BOOKS Programming Collective Intelligence Toby Segaran Recommender Systems Handbook Many Authors Big Data For Dummies Marcia Kaufman, Fern Halper
  37. 37. OPEN SOURCES
  38. 38. Thank you! CONTACT ME: tuanmaster2002@yahoo.com 0938 916 902 http://bloghoctap.com/
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This presentation show the method to build a Recommender System with Collaborative FIltering method.

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