What is Items

With the increasing amount of data produced daily, it becomes very difficult for users to find resources suitable to their needs. Recommendation systems, which are capable of providing individualized suggestions or guiding the user to interesting or relevant resources within a large data space, are proposed for this purpose. In this article, the authors do a comprehensive assessment of recommendation models, propose a categorization scheme, analyze challenges, and explore unresolved issues. In addition, they highlight new trends and future visions in this field of study, emphasizing the need of merging ontologies and machine-learning algorithms to increase the accuracy and efficiency of the recommender systems.