Collaborative Filtering (CF)
Techopedia Explains Collaborative Filtering (CF)For example, a site like Amazon may recommend that the customers who purchase books A and B purchase book C as well. This is done by comparing the historical preferences of those who have purchased the same books.
Different types of collaborative filtering are as follows:
- Memory Based: This method makes use of user rating information to calculate the likeness between the users or items. This calculated likeness is then used to make recommendations.
- Model Based: Models are created by using data mining, and the system learns algorithms to look for habits according to training data. These models are then used to come up with predictions for actual data.
- Hybrid: Various programs combine the model-based and memory-based CF algorithms.
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