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:在这个大数据时代,当代人很难从网上平台内的大量数据中找到正确的数据。在这种情况下,需要建立一个信息过滤系统,以帮助他们找到他们想要的信息。近年来,出现了一个研究领域,称为建议系统。建议者由于拥有许多实际应用而变得非常重要。本文件回顾了电子商务、电子旅游、电子资源、电子政府、电子学习和电子图书馆中推荐者系统的不同技术和发展情况。通过分析有关这一专题的近期工作,我们将能够详细概述当前的发展情况,并找出建议系统中存在的困难。最终结果为从业人员和研究人员提供了对建议系统及其应用的必要指导和深入了解。