- 专利标题: AUTOMATED PREDICTIVE MODELING AND FRAMEWORK
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申请号: US15226196申请日: 2016-08-02
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公开(公告)号: US20170236056A1公开(公告)日: 2017-08-17
- 发明人: Ying Shan , Thomas Ryan Hoens , Jian Jiao , Haijing Wang , Dong Yu , JC Mao
- 申请人: Microsoft Technology Licensing, LLC
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G06F17/30
摘要:
Systems and methods for providing a predictive framework are provided. The predictive framework comprises plural neural layers of adaptable, executable neurons. Neurons accept one or more input signals and produce an output signal that may be used by an upper-level neural layer. Input signals are received by an encoding neural layer, where there is a 1:1 correspondence between an input signal and an encoding neuron. Input signals for a set of data are received at the encoding layer and processed successively by the plurality of neural layers. An objective function utilizes the output signals of the topmost neural layer to generate predictive results for the data set according to an objective. In one embodiment, the objective is to determine the likelihood of user interaction with regard to a specific item of content in a set of search results, or the likelihood of user interaction with regard to any item of content in a set of search results.
公开/授权文献
- US10685281B2 Automated predictive modeling and framework 公开/授权日:2020-06-16
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