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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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Recommender System
How to build a
with Content-base Filtering
Võ Duy TuấnCTO @ 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
Introduction
Content-based Filtering
Question & Answer
AGENDA
1. Introduction
APPLICATIONS
• Personalized recommendation• Social recommendation• Item recommendation• Combination of 3 approaches above
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 Function• Large Feature Set• What is the best K in kNN Algorithm?• Large Data set
ADJUSTMENTS
• Hybrid Recommender System• Sale forecast system• Context of User• Type of Item, Action• External (3rd-party) information.
BOOKS
Data Science for BusinessFoster Provost,Tom Fawcettv
Recommender Systems HandbookMany Authors
Big Data For DummiesMarcia Kaufman, Fern Halper