Invention Grant
- Patent Title: Systems and methods for generating a geo-level hierarchical Bayesian model
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Application No.: US15693326Application Date: 2017-08-31
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Publication No.: US10706191B2Publication Date: 2020-07-07
- Inventor: Yunting Sun , Yuxue Jin , James Koehler , Xiaojing Huang , David Chan , Yueqing Wang , Conor Sontag , Shi Zhong , Luis Gonzalez Perez
- Applicant: Google Inc.
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Foley & Lardner LLP
- Main IPC: H04N21/25
- IPC: H04N21/25 ; G06F30/20 ; G06F17/18 ; H04L29/06 ; G06T7/11 ; G06Q30/02 ; G06F111/10

Abstract:
Systems, methods, and computer-readable storage media that may be used to generate a Bayesian hierarchical model. One method includes generating a plurality of geographic regions by grouping one or more geographic sub-regions into each of the plurality of geographic regions. The method further includes receiving data for the geographic sub-regions, the data including responses, content inputs, content types, and location identifiers. The method further includes generating geo-level data from the received data by grouping the responses and content inputs of the received data based on a correlation of the location identifiers of the received data to the plurality of geographic regions. The method includes fitting a Bayesian hierarchical model based on at least the geo-level data, the content types, and the geographic regions and determining a content input mix for the content types for each geographic region based on the Bayesian hierarchical model and a content input constraint.
Public/Granted literature
- US20190065638A1 SYSTEMS AND METHODS FOR GENERATING A GEO-LEVEL HIERARCHICAL BAYESIAN MODEL Public/Granted day:2019-02-28
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