上下文感知推荐系统和服务的调查

Ebunoluwa Ashley-Dejo, S. Ngwira, T. Zuva
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引用次数: 25

摘要

互联网、移动和无线技术的进步使信息在数量和可访问性方面发生了迅速变化。海量的信息可能是毁灭性的,尤其是对移动用户来说,这超出了人类区分相关和不相关信息的能力。多年来,推荐系统已经广为人知,并在电子学习、网上购物、旅游等各个领域进行了研究,以帮助克服信息过载。推荐是基于对特定事物或物品感兴趣的用户产生的。通过结合时间、天气和地点等上下文,进一步增强了该推荐过程,使推荐更加准确和有效。然而,这些系统引入了上下文感知推荐系统。本文介绍了上下文感知推荐系统的研究概况、上下文感知推荐系统的背景和算法,并讨论了上下文感知推荐系统存在的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A survey of Context-aware Recommender System and services
The advancement of the Internet, mobile and wireless technologies have produced a rapid change of information in terms of volume and accessibility. The enormous volume of information can be devastating especially to mobile users exceeding human ability to differentiate information which is relevant and that which is irrelevant. For many yzears now, recommender system have become well-known, and have been studied in various domains such as e-learning, online shopping, tourism to help overcome information overload. Recommendations are produced based on users who have interests in a particular thing or item. This recommendation process was further enhanced by incorporating context such as time, weather, and location to make recommendations more accurate and efficient. However, these systems have introduced context-aware recommender systems. This paper presents a survey of Context-aware recommender systems, the background and algorithms of Context-aware Recommender System, and also discusses the open issues of context-aware recommender systems.
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