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1. 发明公开

EP3166025A1 IDENTIFYING CONTENT ITEMS USING A DEEP-LEARNING MODEL 无效
标题翻译：吸烟者密歇根大学深潜训练
公开(公告)号：EP3166025A1
公开(公告)日：2017-05-10
申请号：EP16169502.8
申请日：2016-05-13
申请人： Facebook, Inc.
发明人： Bourdev, Lubomir Dimitrov , Paluri, Balmanohar , Rippel, Oren , Dollar, Piotr
IPC分类号： G06F17/30 , G06Q50/00 , G06K9/62
CPC分类号： G06Q50/01 , G06F17/30244 , G06K9/00624 , G06K9/4628 , G06K9/6218 , G06K9/6271
摘要： In one embodiment, a method may include receiving a first content item. A first embedding of the first content item may be determined and may correspond to a first point in an embedding space. The embedding space may include a plurality of second points corresponding to a plurality of second embeddings of second content items. The embeddings are determined using a deep-learning model. The points are located in one or more clusters in the embedding space, which are each associated with a class of content items. Locations of points within clusters may be based on one or more attributes of the respective corresponding content items. Second content items that are similar to the first content item may be identified based on the locations of the first point and the second points and on particular clusters that the second points corresponding to the identified second content items are located in.
摘要翻译：在一个实施例中，一种方法可以包括接收第一内容项。可以确定第一内容项的第一嵌入，并且可以对应于嵌入空间中的第一点。嵌入空间可以包括对应于第二内容项的多个第二嵌入的多个第二点。使用深度学习模型确定嵌入。点位于嵌入空间中的一个或多个集群中，每个集群都与一类内容项相关联。集群内的点的位置可以基于相应的相应内容项的一个或多个属性。可以基于第一点和第二点的位置以及对应于所识别的第二内容项目的第二点所在的特定集群来识别与第一内容项目相似的第二内容项目。

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