电子商务中的推荐系统

Sanjeevan Sivapalan, A. Sadeghian, H. Rahnama, A. M. Madni
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引用次数: 566

摘要

互联网正在加速和改变人们完成日常任务的方式,比如网上购物、支付水电费、看新电影、交流等。例如,在旧的购物方式中,产品是为单一市场和受众大量生产的,但这种方式已不再可行。基于长产品和开发周期的市场将不复存在。为了保持竞争力,市场需要为不同需求的不同客户提供不同的产品和服务。向网上购物的转变使得生产商和零售商有责任根据客户的需求进行定制,同时提供比以前更多的选择。然而,这给客户带来了一个问题,他们现在必须分析每一个产品,以确定他们真正需要的是什么,并从中受益。为了在这种情况下帮助客户,我们讨论了常用的推荐系统技术及其相关的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recommender systems in e-commerce
Internet is speeding up and modifying the manner in which daily tasks such as online shopping, paying utility bills, watching new movies, communicating, etc., are accomplished. As an example, in older shopping methods, products were mass produced for a single market and audience but that approach is no longer viable. Markets based on long product and development cycles can no longer survive. To stay competitive, markets need to provide different products and services to different customers with different needs. The shift to online shopping has made it incumbent on producers and retailers to customize for customers' needs while providing more options than were possible before. This, however, poses a problem for customers who must now analyze every offering in order to determine what they actually need and will benefit from. To aid customers in this scenario, we discuss about common recommender systems techniques that have been employed and their associated trade-offs.
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