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，当前一代用户难以从在线平台海量数据中准确找到所需数据。在此背景下，亟需一种能帮助用户定位目标信息的信息过滤系统。近年来，一个被称为推荐系统的研究领域应运而生。推荐系统因其在现实生活中的广泛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、电子学习及电子图书馆等领域的各项技术与进展。通过分析该主题的最新研究成果，我们将能够全面概述当前的发展动态，并识别推荐系统中存在的现有难题。最终成果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。