Dealing with Pure New User Cold-Start Problem in Recommendation System Based on Linked Open Data and Social Network Features

Algorithm 3

Weighted average recommendation.

	Input: User Profile, Item Clusters I, User Cluster U, User-Item Matrix
	Output: N Items recommended to new user
(1)	When a new user logs in to the system, his profile will be generated by the system using “User Profile Generation” module.
(2)	Then classifier will analyze the user and can predict the “User Cluster” to which this new user belongs to.
(3)	Once the “User Cluster” is found to which new user belongs to, system will analyze the rating provided to each “Item cluster” by only those users who are present in this predicted “User Cluster.”
(4)	The average weight of the rating given to each Item cluster by the user present in the predicted cluster is calculated.
(5)	Item cluster with highest rating value is recommended to the new user.