-
公开(公告)号：US20200213201A1
公开(公告)日：2020-07-02
申请号：US16232357
申请日：2018-12-26
发明人： Divya Venugopalan , Yiou Xiao , Lingjie Weng , Heloise Logan , Aastha Jain , Mahdi Shafiei
摘要： In an embodiment, the disclosed technologies include computing a score for a node pair including first and second nodes of a digital connection graph; where nodes of the digital connection graph represent members of an online system; where the online system uses the digital connection graph to determine a runtime decision related to a member represented by the first node; where the score indicates a predicted likelihood of interaction, during a time interval, after a digital connection between the first and second nodes of the node pair; where the predicted likelihood of interaction is determined by comparing a set of statistics computed for the node pair to a digital model; where the digital model has been created using data extracted from post-connection interactions in the online system between members whose nodes are connected in the digital connection graph; causing the score to modify the runtime decision.
-
公开(公告)号：US20190197398A1
公开(公告)日：2019-06-27
申请号：US15855912
申请日：2017-12-27
发明人： Mohsen Jamali , Hamed Firooz , Samaneh Moghaddam , Mahdi Shafiei
IPC分类号： G06N3/08
CPC分类号： G06N3/08 , G06Q10/1053
摘要： Techniques for learning and leveraging embeddings for response prediction are provided. Based on training data, an embedding for each attribute value of multiple content items is generated, an embedding for each attribute value of multiple entities is generated, weights of a first neural network for content items is generated, and weights of a second neural network for requesting entities is generated. In response to receiving a request, a particular content item is identified. A first set of embeddings for the particular content item is identified and input into the first neural network to generate first output. A particular requesting entity that initiated the content request is identified. A second set of embeddings for the particular requesting entity is identified and input into the second neural network to generate second output. The particular content item is selected based on the first output and the second output.
-
搜索结果
2 条记录 (耗时 0.015 秒)