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Recommender
System
How to build a
with Content-base Filtering
Võ Duy Tuấn
CTO @ spiral.vn
 PHP 5 Zend Certified Engineer
 Mobile App Developer
 Web Developer & Designer
 Interest:
...
Introduction
Content-based Filtering
Question & Answer
AGENDA
1. Introduction
APPLICATIONS
• Personalized recommendation
• Social recommendation
• Item recommendation
• Combination of 3 approaches abo...
AMAZON.COM | BOOKS
PLAY.GOOGLE.COM | APPS
SKILLSHARE.COM | CLASSES
PROCESS DIAGRAM
Preprocessing Data Analysis Adjustment
INPUT OUTPUT
TYPE OF RECOMMENDER SYSTEM
• Collaborative filtering
• Content-based filtering
• Hybrid
2. Content-based
Filtering
Collaborative Filtering Crash-course
Read more: www.slideshare.net/lonelywolf/how-to-build-a-recommender-system
OBJECT
OBJECT INFORMATION
FEATURE SET
SIMILARITY MATRIX
SIMILARITY MEASURE
SIMILARITY MEASURE
SIMILARITY MATRIX
SIMILARITY SORTING
K-NEAREST NEIGHBOR (knn)
Problem ?!
PROBLEMS
• Explore New Features
• Build feature data for item
• Feature Weighting
• Feature Value Distance Measure Functio...
ADJUSTMENTS
• Hybrid Recommender System
• Sale forecast system
• Context of User
• Type of Item, Action
• External (3rd-pa...
BOOKS
Data Science for Business
Foster Provost,Tom Fawcettv
Recommender Systems
Handbook
Many Authors
Big Data For Dummies...
Thank you!
CONTACT ME:
tuanmaster2012@gmail.com
0938 916 902
http://bloghoctap.com/
How to Build Recommender System with Content based Filtering
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How to Build Recommender System with Content based Filtering

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How to build recommender system. Content based filtering method for recommender system. Feature weighting and feature measure function.

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Transcript of "How to Build Recommender System with Content based Filtering"

  1. 1. v Recommender System How to build a with Content-base Filtering
  2. 2. Võ Duy Tuấn CTO @ spiral.vn  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 Content-based 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. Content-based Filtering
  12. 12. Collaborative Filtering Crash-course Read more: www.slideshare.net/lonelywolf/how-to-build-a-recommender-system
  13. 13. OBJECT
  14. 14. OBJECT INFORMATION
  15. 15. FEATURE SET
  16. 16. SIMILARITY MATRIX
  17. 17. SIMILARITY MEASURE
  18. 18. SIMILARITY MEASURE
  19. 19. SIMILARITY MATRIX
  20. 20. SIMILARITY SORTING
  21. 21. K-NEAREST NEIGHBOR (knn)
  22. 22. Problem ?!
  23. 23. PROBLEMS • Explore New Features • Build feature data for item • Feature Weighting • Feature Value Distance Measure Function • Large Feature Set • What is the best K in kNN Algorithm? • Large Data set
  24. 24. ADJUSTMENTS • Hybrid Recommender System • Sale forecast system • Context of User • Type of Item, Action • External (3rd-party) information.
  25. 25. BOOKS Data Science for Business Foster Provost,Tom Fawcettv Recommender Systems Handbook Many Authors Big Data For Dummies Marcia Kaufman, Fern Halper
  26. 26. Thank you! CONTACT ME: tuanmaster2012@gmail.com 0938 916 902 http://bloghoctap.com/
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