Covers: theory of Content Based Recommendations
Estimated time needed to finish: 30 minutes
Questions this item addresses:
  • High level function of a content based recommendation system
How to use this item?

Read Section 4.1 of the book

Author(s) / creator(s) / reference(s)
Charu Aggarwal
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Introduction to Content Based Recommender Systems

Contributors
Total time needed: ~2 hours
Objectives
Techniques and algorithms for doing content based recommendations
Potential Use Cases
Recommending web pages / products
Who is This For ?
INTERMEDIATEML Engineer or Data Scientist with some high level knowledge of recommender systems
Click on each of the following annotated items to see details.
BOOK_CHAPTER 1. Introduction to content based recommendation systems
  • High level function of a content based recommendation system
30 minutes
BOOK_CHAPTER 2. Feature extraction and cleaning
  • How to extract features from unstructured text
30 minutes
BOOK_CHAPTER 3. Supervised Feature Extraction and Weighting
  • Algorithms for how to extract discriminative features using labelled data
30 minutes
ARTICLE 4. Learning user profiles
  • How to learn user profiles and actions to make recommendations to users
10 minutes

Concepts Covered

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