An investigation of the techniques implemented by recommender systems.

Online reviews are a popular way for buyers to learn more about products before making a purchase decision. These reviews are based on the opinions of both former consumers and experts. The quantity of reviews submitted by people has recently increased. It is a crucial aspect of the answer to information overload that recommender systems provide users with more useful and customized information services. Collaborative filtering techniques are critical components of recommender systems because they influence the tastes of communities of users who are similar to one another, resulting in high-quality recommendations [ABSTRACT FROM AUTHOR]