设计一个基于社交网络和位置服务的推荐系统

Fatemeh Khoshnood, M. Mahdavi, M. Kiani
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引用次数: 15

摘要

移动设备减少了空间限制,人们可以在适当的框架中个性化内容,考虑到个人的位置并呈现它。然而,仅使用基于地点的服务,不可能在提供的建议中考虑用户的兴趣和偏好。当前这一代的基于地点的服务并没有为用户提供个性化的建议,而是根据用户与所在地点的距离,提供与用户兴趣接近的建议。为了解决这一问题,本文讨论了使用具有识别用户兴趣和偏好能力的社交推荐系统的想法,并根据这些兴趣和偏好以及用户当前的位置提出了一些建议。社交推荐系统是网络社交数据的组合;用户的社交网络和空间信息。因为用户的信息包含了社交网站中的个人信息和兴趣,考虑到用户当前的位置和社交网络数据库中存在的信息,有可能为用户提供合适的建议。通过这种方式,用户的交互减少,用户可以获得自己喜欢的信息和服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DESIGNING A RECOMMENDER SYSTEM BASED ON SOCIAL NETWORKS AND LOCATION BASED SERVICES
Mobile devices have diminished spatial limitations, in a way that one can personalize content in a suitable frame considering individual’s location and present it. Yet, it is not possible to consider user’s interests and preferences in a suggestion provided using just place-based services. Current generation of place-based services do not provide users with personalized suggestions, instead they just offer suggestions close to interests based on users distance from the place where they are. In order to solve this problem, the idea of using social recommender systems was discussed which contains capability of identifying user’s interests and preferences and based on them and user’s current place, it offers some suggestions. Social recommender systems are a combination of social data on web like; user’s social networks and spatial information. Because user’s information include personal information and interests in social network sites, considering user’s current location and the information existing in social network data base, it is possible to provide user with a suitable suggestion. Through this method users’ interaction decreases and they can acquire their favorite information and services.
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