上下文感知推荐系统框架、技术和应用:综述

Hamdy Fadl Abdulkarem, Ghada Y. Abozaid, M. Soliman
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引用次数: 9

摘要

为移动用户量身定制的服务或信息变得非常重要;由于移动用户在各种活动中可以获得大量的信息和服务。推荐系统可以与上下文感知相结合,根据用户当前的上下文和个人资料,为用户提供量身定制的服务、信息和学习资源。上下文感知推荐系统具有多种用途,许多应用和服务都依赖于上下文感知推荐系统,目前上下文感知推荐系统在各个领域得到了广泛的应用。本文介绍了cas的概述、框架、技术、算法和应用。此外,本文还对cars的一般问题进行了讨论,并对提出的解决方案进行了探讨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Context-Aware Recommender System Frameworks, Techniques, and Applications: A Survey
Tailored services or information for mobile users became very crucial; due to the enormous amount of information and services that are available for mobile users during their various activities. Recommendation system can be merged with context awareness to provide tailored services, information, moreover learning resources for users, based on their current context and profile. Context Aware Recommendation Systems (CARSs) have various usages also many applications and services depend on it, CARSs nowadays become widely used in various domains. This paper presents a survey of CARSs overview, frameworks, techniques, algorithms, and applications. Moreover, the paper discusses the issues of CARSs in general and investigates the proposed solutions.
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