论文标题

推荐系统技术和电子商务领域的调查

A Survey of Recommender System Techniques and the Ecommerce Domain

论文作者

Hossain, Imran, Palash, Md Aminul Haque, Sejuty, Anika Tabassum, Tanjim, Noor A, Nasim, MD Abdullah AL, Saif, Sarwar, Suraj, Abu Bokor, Haque, Md Mahim Anjum, Karim, Nazmul

论文摘要

在这个大数据时代,当前一代很难从在线平台中包含的大量数据中找到正确的数据。在这种情况下,需要一个信息过滤系统,可以帮助他们找到所需的信息。近年来,出现了一个称为推荐系统的研究领域。推荐人变得重要,因为他们拥有许多现实生活中的应用。本文回顾了推荐系统在电子商务,电子商务,电子资源,电子政务,电子学习和电子生活中的不同技术和发展。通过分析有关此主题的最新工作,我们将能够详细概述当前的发展,并确定建议系统中的现有困难。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见解。

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.

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