Invention Grant
- Patent Title: Automated predictive modeling and framework
-
Application No.: US15226196Application Date: 2016-08-02
-
Publication No.: US10685281B2Publication Date: 2020-06-16
- Inventor: Ying Shan , Thomas Ryan Hoens , Jian Jiao , Haijing Wang , Dong Yu , JC Mao
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Ranck IP Law
- Agent Jeffrey L. Ranck
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F16/951 ; G06Q30/02 ; G06Q10/04 ; G06N3/04

Abstract:
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.
Public/Granted literature
- US20170236056A1 AUTOMATED PREDICTIVE MODELING AND FRAMEWORK Public/Granted day:2017-08-17
Information query