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.

翻译：在大数据时代，当前世代难以从在线平台所包含的海量数据中精准找到所需信息。在此背景下，亟需一种信息过滤系统以帮助用户获取目标信息。近年来，一个被称为推荐系统的研究领域应运而生。推荐系统因具有众多实际应用而变得日益重要。本文综述了推荐系统在电子商务、电子旅游、电子资源、电子政务、在线教育及数字图书馆等领域的各项技术及其发展。通过分析该主题的最新研究成果，我们将能全面概述当前进展，并识别推荐系统中存在的现有难题。最终结论为从业者和研究者提供了关于推荐系统及其应用的必要指导与深刻见解。