Abstract:
Recommender System forms a specific type
of information filtering (IF) technique that
attempts to present information items that are
likely of interest to the user. Furthermore,
accuracy is the fundamental dimension for the
effectiveness of recommender systems.
Collaborative filtering system collects evaluations
from users for quality and relevance of stored
items. This system categorizes items based on the
user’s ratings of the item instead of the item
descriptions.User-based CF systems compare a
target user’s choice with those of other users to
identify a group of similar-minded people. This
system is implemented by using Pearson
correlation algorithm and Prediction algorithm in
user-based collaborative filtering to recommend
the customer needed item. Finally, this system
calculates Mean Absolute Error (MAE) to express
the customer satisfaction
