Location based recommender systems: Architecture, trends and research areas

Sunita Tiwari, Saroj Kaushik, Shivendra Tiwari, Priti Jagwani
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引用次数: 12

Abstract

The growths of Internet, Global Positioning System (GPS) and wireless telecommunication technologies have opened new avenues in potential area of mobile computing called Location Based Services (LBS). Recommendation of personalized information / services in location based services has become an attractive trend for success of businesses. A Recommender System attempts to solve the problem of information overload and provides product and service recommendation based on user profile and preferences. The location of the user is an important information item that can be associated to the existing user profile in order to provide efficient recommendations. Also, easy availability of GPS enabled devices brings a large amount of GPS trajectories representing user's mobile logs. These GPS trajectories can be used to mine interesting patterns about users. We have studied the utility and application of information extracted from user's GPS trajectory data in recommender systems. We conceive that recommendation has an intrinsic social component and therefore this work takes a perspective towards the social aspect in location based recommender systems. In this paper, we are presenting the state-of-the-art research trends, challenges and applications in the area of Location-Based Recommender Systems (LBRS). (8 pages)
基于位置的推荐系统:架构、趋势和研究领域
互联网、全球定位系统(GPS)和无线通信技术的发展为移动计算的潜在领域——基于位置的服务(LBS)——开辟了新的途径。在基于位置的服务中,个性化信息/服务的推荐已经成为企业成功的一个诱人趋势。推荐系统试图解决信息过载的问题,并根据用户的个人资料和偏好提供产品和服务推荐。用户的位置是一个重要的信息项,它可以与现有的用户配置文件相关联,以便提供有效的推荐。此外,GPS设备的易用性带来了大量代表用户移动日志的GPS轨迹。这些GPS轨迹可以用来挖掘关于用户的有趣模式。我们研究了从用户GPS轨迹数据中提取信息在推荐系统中的实用性和应用。我们认为推荐具有内在的社交成分,因此这项工作从社交方面研究了基于位置的推荐系统。在本文中,我们介绍了基于位置的推荐系统(LBRS)领域的最新研究趋势、挑战和应用。(8页)
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