  In this big data era, it is hard for the current generation to find the right
data from the huge amount of data contained within online platforms. In such a
situation, there is a need for an information filtering system that might help
them find the information they are looking for. In recent years, a research
field has emerged known as recommender systems. Recommenders have become
important as they have many real-life applications. This paper reviews the
different techniques and developments of recommender systems in e-commerce,
e-tourism, e-resources, e-government, e-learning, and e-library. By analyzing
recent work on this topic, we will be able to provide a detailed overview of
current developments and identify existing difficulties in recommendation
systems. The final results give practitioners and researchers the necessary
guidance and insights into the recommendation system and its application.

Information Retrieval;Artificial Intelligence