A Survey on Recommender Systems Challenges and Solutions

A recommender system is a set of tools for information retrieval. It improves access and proactively recommends items and services that match users' tastes by considering their explicit and implicit preferences and behaviors. Recommender systems have become very popular in the e-commerce field. Today, the internet is flooded with diverse information that makes it very difficult for the end-users to reach out for what they need. Recommender systems provide tailored views to users who are constantly adapted to the users' changing tastes. Although many recommendation techniques have been developed in multiple domains, recommender systems still face problems and challenges that hinder their precision. This paper provides a comprehensive summary of the key challenges and problems when developing recommender systems and summarizes the latest research achievements and directions to resolve them. In addition to that, we go beyond this by presenting the evaluation techniques used to judge the performance of recommender systems.