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首页> 外文会议>International conference on communications and cyber physical engineering >Survey Paper on New Approach to Location Recommendation Using Scalable Content-Aware Collaborative Filtering
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Survey Paper on New Approach to Location Recommendation Using Scalable Content-Aware Collaborative Filtering

机译：关于使用可扩展的内容感知协作过滤的位置推荐新方法的调查报告

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摘要

The Location recommendation playing a important role for finding interesting places. Although recently researching he has advise places and provide information using socially and geographically, some of which have dealt with the problem of starting the new cold user. The Records of mobility shared on a social networks. Collaborative content-based filters based on explicit comments, but require a negative design sample for a improving performance. negative user preferences not observable in mobility records. However, In previous studies that sampling-based methods and this method does not work well. A Propose system based on implicit scalable comments Content-based collaborative filtering framework is used to avoid negative sampling and incorporate semantic based contents. Algorithm of Optimization is used to major in a linear fashion with the dimensions of the data and the dimensions of the features, dimensions of latent space is represent in a quadratic way. Also established relationship with factorization of the plate matrix plating. Personalized recommendation recommends the Point Of Interest routes by mining users travel records. Finally, evaluated ICCF framework with large-scale Location Based Social Network data set in which users have text and profiles.
机译：位置推荐对于寻找有趣的地方起着重要作用。尽管最近进行了研究，但他已从社会和地理角度建议了地点并提供了信息，其中一些解决了开始新的冷用户的问题。在社交网络上共享的出行记录。基于显式注释的基于内容的协作过滤器，但是需要否定设计示例才能提高性能。否定性用户偏好在移动记录中无法观察到。但是，在以前的研究中，基于采样的方法和这种方法效果不佳。基于隐式可伸缩注释的基于内容的协作过滤框架的Propose系统可避免负采样，并包含基于语义的内容。优化算法用于线性地处理数据的维数和特征的维数，以二维方式表示潜在空间的维数。还建立了与板基质镀层分解的关系。个性化建议通过挖掘用户的旅行记录来推荐兴趣点路线。最后，评估了具有大型基于位置的社交网络数据集的ICCF框架，其中用户具有文本和个人资料。

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