- 专利标题: COMPRESSION OF USER INTERACTION DATA FOR MACHINE LEARNING-BASED DETECTION OF TARGET CATEGORY EXAMPLES
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申请号: US17330029申请日: 2021-05-25
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公开(公告)号: US20220385689A1公开(公告)日: 2022-12-01
- 发明人: Vivek Rajasekharan , Seyed Amir Mir Bagheri , James Pratt
- 申请人: AT&T Intellectual Property I, L.P.
- 申请人地址: US GA Atlanta
- 专利权人: AT&T Intellectual Property I, L.P.
- 当前专利权人: AT&T Intellectual Property I, L.P.
- 当前专利权人地址: US GA Atlanta
- 主分类号: H04L29/06
- IPC分类号: H04L29/06 ; G06N3/04 ; G06N3/08
摘要:
A processing system may identify a plurality of user interaction data associated with a target category of a plurality of users, identify a relevant subset of user interaction data, compress the plurality of user interaction data to the relevant subset of user interaction data, train a machine learning model with the relevant subset of user interaction data, obtain additional user interaction data associated with an additional user, identify a relevant subset of the additional user interaction data, apply the relevant subset of the additional user interaction data as an input to the machine learning model, obtain an output of the machine learning model quantifying a measure of which the relevant subset of the additional user interaction data is indicative of the target category, and perform at least one action responsive to the measure of which the relevant subset of the additional user interaction data is indicative of the target category.
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