Exploiting Past Users’ Interests and Predictions in an Active Learning Method for Dealing with Cold Start in Recommender Systems

Exploiting Past Users’ Interests and Predictions in an Active Learning Method for Dealing with Cold Start in Recommender Systems

This paper focuses on the new users cold-start issue in the context of recommender systems. New users who do not receive pertinent recommendations may abandon the system. In order to cope with this issue, we use active learning techniques. These methods engage the new users to interact with the syst...

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Bibliographic Details
Main Authors: Manuel Pozo, Raja Chiky, Farid Meziane, Elisabeth Métais
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Informatics
Subjects:
cold start
recommender systems
active learning
collaborative filtering
Online Access:http://www.mdpi.com/2227-9709/5/3/35

Internet

http://www.mdpi.com/2227-9709/5/3/35

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