Recommendation Systems an overview, Types, Algorithms and Artificial Intelligence

Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine. They have become fundamental applications in electronic commerce and information access, providing suggestions that effectively prune large information spaces so that users are directed toward those items that best meet their needs and preferences. In this work, we will provide a brief review of different recommender systems’ algorithms, which play an important role in the Internet world and are used in many applications. The recommendation system is a system that learns from the user’s previous actions and predicts their current preferences and generally is categorized into four Main classes; these include Collaborative Filtering, Content-based, Knowledge-based, and hybrid-based Approach. We shall review and classify the main types of Recommendation Techniques and the (A.I) methods used in them . The paper also elaborates on these approaches and their techniques with their limitations and advantages as well as the challenges and Problems faced by the recommendation systems.