Course Content
Association Rule Mining
Association Rule Mining
Recommendation Systems
Recommendation systems are algorithms designed to suggest items or content to users based on their preferences, behaviors, or similarities with other users.
Association Rule Mining (ARM) is a technique used in recommendation systems to uncover patterns in transaction data. By analyzing user-item interactions, ARM identifies associations such as "users who buy X
also tend to buy Y
," enabling personalized recommendations.
For example, if a user has purchased item X
, the system can recommend item Y
based on this association.
This enhances the shopping experience by offering relevant suggestions based on individual preferences and behaviors.
Example
Let's discover a code example that demonstrates a simple recommendation system using Association Rule Mining:
As a result, we can conclude that if a person has purchased all these items: {'beef', 'apples', 'bread'}, we can recommend them to purchase all the goods provided in the result of the code sample execution.
Everything was clear?