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What is Collaborative Filtering in Recommender Systems about?

This document provides an introduction and overview of collaborative filtering for recommender systems. It discusses how collaborative filtering works by finding similar users based on their item ratings. There are two types of collaborative filtering - user-based, which finds similar users to a target user, and item-based, which finds similar items. The process involves forming neighborhoods of similar users or items, then using the ratings from those neighbors to predict ratings for new items. Pearson

Author

sudipta244703

Language

EN