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公开(公告)号:US20180253637A1
公开(公告)日:2018-09-06
申请号:US15446870
申请日:2017-03-01
发明人: Feng Zhu , Xinying Song , Chao Zhong , Shijing Fang , Ryan Bouchard , Valentine N. Fontama , Prabhdeep Singh , Jianfeng Gao , Li Deng
CPC分类号: G06N3/0445 , G06N3/0454 , G06N3/08 , H04L67/22
摘要: A method to predict churn includes obtaining static features representative of a customer of a service, obtaining time series features representative of the customers interaction with the service, using a deep neural network to process the static features, using a recurrent neural network to process the time series features; and combining outputs from the deep neural network and the recurrent neural network to predict likelihood of customer churn.