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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：使用可扩展内容感知协作过滤的新方法的调查论文

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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：位置推荐在寻找有趣的地方发挥着重要作用。虽然最近研究他已经建议了地方并提供了使用社交和地理位置的信息，其中一些已经处理了启动新的冷用户的问题。在社交网络上共享的移动性记录。基于合作内容的基于显式评论的滤波器，但需要一个负面设计样本，以提高性能。流动性记录中未观察到的负用户偏好。然而，在以前的研究中，基于采样的方法和这种方法不起作用。基于隐式可伸缩评论的基于内容的协作滤波框架的提议系统用于避免负对采样并包含基于语义的内容。优化算法用于以线性方式主要具有数据的尺寸和特征的尺寸，潜在空间的尺寸以二次方式表示。还建立了与板矩阵电镀的分解关系的关系。个性化建议通过采矿用户旅行记录推荐利息路线。最后，评估了具有基于大型位置的社交网络数据集的ICCF框架，用户拥有文本和配置文件。

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