Collaborative Filtering

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Definition: Collaborative Filtering

Collaborative Filtering is a technique used by the firms implementing e-commerce or online platforms. Collaborative filtering is incorporated into the system or platform’s recommender system in order to facilitate upselling to the customer. In this, the preference of a user is matched against the preferences of similar users or based upon historical data or buying patterns and the customers are offered other products sold at the same platform or by the same firm.

Collaborative filtering can be done in 3 ways –

  1. Memory Based – this implements a user rating mechanism which helps categorise customer profiles and on that basis offer recommendations
  2. Model Based – data is stored and algorithms are incorporated in the models to capture buying habits and patterns which are used to come up with predictions
  3. Hybrid – combination of the above

Example: For example, on visiting Amazon, Flipkart or other such websites, based on my buying patterns or match of my preferences to other groups of users, the system generates recommendations in order to upsell by introducing products according to my preferences.

Hence, this concludes the definition of Collaborative Filtering along with its overview.

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