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2. 发明申请

US20120219191A1 LOCAL METRIC LEARNING FOR TAG RECOMMENDATION IN SOCIAL NETWORKS 有权
标题翻译：在社会网络中进行标签推荐的本地学习方法
公开(公告)号：US20120219191A1
公开(公告)日：2012-08-30
申请号：US13036209
申请日：2011-02-28
申请人： Mohamed Aymen Benzarti , Boris Chidlovskii , Nishant Vijayakumar
发明人： Mohamed Aymen Benzarti , Boris Chidlovskii , Nishant Vijayakumar
IPC分类号： G06K9/00 , G06F15/16
CPC分类号： G06Q30/0201 , G06K9/00677 , G06Q50/01
摘要： A tag recommendation for an item to be tagged is generated by: selecting a set of candidate neighboring items in an electronic social network based on context of items in the electronic social network respective to an owner of the item to be tagged; selecting a set of nearest neighboring items from the set of candidate neighboring items based on distances of the candidate neighboring items from the item to be tagged as measured by an item comparison metric; and selecting at least one tag recommendation based on tags of the items of the set of nearest neighboring items. The item comparison metric may comprise a Mahalanobis distance metric trained on the set of candidate neighboring items to correlate the trained Mahalanobis distance between pairs of items of the set of candidate neighboring items with an overlap metric indicative of overlap of the tag sets of the two items.
摘要翻译：通过以下方式生成要标记的商品的标签推荐：基于与要标记的商品的所有者相关联的电子社交网络中的项目的上下文来选择电子社交网络中的一组候选邻居项目; 基于通过项目比较度量测量的候选相邻项目与要标记的项目的距离，从所述候选相邻项目集合中选择一组最近邻项目; 以及基于所述一组最近邻项目的项目的标签来选择至少一个标签推荐。项目比较度量可以包括在所述候选相邻项目的集合上训练的马哈拉诺比斯距离度量，以将所述候选相邻项目组中的项目对之间的训练马哈拉诺比斯距离与指示两个项目的标签组的重叠的重叠度量相关联。

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