A Review of the Role of Sensors in Mobile Context-Aware Recommendation Systems
A Review of the Role of Sensors in Mobile Context-Aware Recommendation Systems
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DOI：
10.1155/2015/489264
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发表时间：
2015-01-01
影响因子：
2.3
通讯作者：
del Carmen Rodriguez-Hernandez, Maria
中科院分区：
文献类型：
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作者：
Ilarri, Sergio;Hermoso, Ramon;del Carmen Rodriguez-Hernandez, Maria
推荐系统专门针对用户可能感兴趣的不同类型的特定项目(例如，书籍、电影、餐馆和酒店)提供建议。由于它们的好处和商业利益，它们吸引了相当多的研究关注。特别是，近年来，上下文感知推荐系统的概念似乎强调了考虑用户所涉及的情况的上下文以便提供更准确的推荐的重要性。上下文的检测需要使用不同类型的传感器，这些传感器测量不同的上下文变量。尽管传感器在上下文感知推荐系统的开发中扮演着相关的角色，但传感器和推荐方法通常是独立研究的两个领域。本文对传感器在推荐系统中的应用进行了综述。我们的贡献可以从双重角度来看。一方面，我们概述了现有的用于检测可能与推荐相关的上下文因素的技术。另一方面，我们通过考虑不同的推荐用例和场景来说明传感器的兴趣。
Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios.