Recommender Systems: Making Choices Easier
Recommender systems, like those on Amazon or Netflix, simplify your choices by suggesting products or content based on your past actions. While Amazon focuses on items you've rated or bought, Netflix gears recommendations around your past movie choices, even categorizing by genre. These systems serve two core functions:
- Personalized Suggestions: The algorithms use your history to display products or content you're likely to enjoy.
- Contextual Recommendations: These are short-term suggestions based on your current activity. For instance, Amazon's "people who bought this also bought" feature.
Two popular methods make this possible:
- User-Based Collaborative Filtering: Compares you to similar users to recommend items.
- Item-Based Collaborative Filtering: Looks at items similar to the ones you've interacted with.
The aim? Helping you discover new things effortlessly.