Survey on Recommender Systems Incorporating Trust
Megha Raizada · 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC) · 2022
Large amount of information generated on the web is useful for extracting useful patterns about customers and their purchases. Recommender system provides framework to utilize this information to make suggestions to user according to their previous preferences. They are intelligent systems having decision making capabilities. This in turn enhances business profit. Recommender system endure from problems like cold start, fake profile generation and data sparsity. Inclusion of trust in recommender system helps to alleviate these problems to a great extent. The phenomenon of trust is derived from daily life exp eriences like believing the views/reviews suggested by friends and relatives for buying new things. The desideratum of this research pap er is to procure a survey on how trust can be incorporated in recommender systems and the advantages trust aware recommender sy stems have over traditional recommender systems. It highlights the techniques that have been used to develop trust aware recommenders and pros and cones of these techniques.