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首页> 外文期刊>International Journal of Information Technology and Computer Science >Location Based Recommendation for Mobile Users Using Language Model and Skyline Query
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Location Based Recommendation for Mobile Users Using Language Model and Skyline Query

机译:使用语言模型和天际线查询的移动用户基于位置的推荐

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Location based personalized recommendation has been introduced for the purpose of providing a mobile user with interesting information by distinguishing his preference and location. In most cases, mobile user usually does not provide all attributes of his preference or query. In extreme case, especially when mobile user is moving, he even does not provide any preference or query. Meanwhile, the recommendation system database also does not contain all attributes that can express what the user needs. In this paper, we design an effective location based recommendation system to provide the most possible interesting places to a user when he is moving, according to his implicit preference and physical moving location without the user’s providing his preference or query explicitly. We proposed two circle concepts, physical position circle that represents spatial area around the user and virtual preference circle that is a non-spatial area related to user’s interests. Those skyline query places in physical position circle which also match mobile user’s implicit preference in virtual preference circle will be recommended. User’s implicit preference will be estimated under language modeling framework according to user’s historical visiting behaviors. Experiments show that our method is effective in recommending interesting places to mobile users. The main contribution of the paper comes from the combination of using skyline query and information retrieval to do an implicit location-based personalized recommendation without user’s providing explicit preference or query.
机译:已经引入了基于位置的个性化推荐,其目的是通过区分移动用户的偏好和位置来为其提供有趣的信息。在大多数情况下,移动用户通常不提供其偏好或查询的所有属性。在极端情况下,尤其是在移动用户正在移动时,他甚至不提供任何首选项或查询。同时,推荐系统数据库也不包含可以表达用户需求的所有属性。在本文中,我们设计了一个有效的基于位置的推荐系统,可以根据用户的隐式偏好和实际移动位置向用户提供最可能有趣的地点,而无需用户明确提供其偏好或查询。我们提出了两个圆的概念:代表用户周围空间区域的物理位置圆和代表用户兴趣的非空间区域虚拟偏好圆。建议您在物理位置圈中的那些天际线查询位置也与虚拟偏好圈中移动用户的隐式偏好相匹配。用户的隐性偏好将在语言建模框架下根据用户的历史访问行为进行估算。实验表明,我们的方法可以有效地向移动用户推荐有趣的地方。该论文的主要贡献在于结合了使用天际线查询和信息检索来进行隐式基于位置的个性化推荐,而无需用户提供明确的偏好或查询。

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