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公开(公告)号:US11575632B2
公开(公告)日:2023-02-07
申请号:US16729813
申请日:2019-12-30
Applicant: Oath Inc.
Inventor: Wei Chu , Martin Zinkevich , Lihong Li , Achint Oommen Thomas , Belle Tseng
Abstract: Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.
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公开(公告)号:US20180255012A1
公开(公告)日:2018-09-06
申请号:US15973130
申请日:2018-05-07
Applicant: Oath Inc.
Inventor: Wei Chu , Martin Zinkevich , Lihong Li , Achint Oommen Thomas , Belle Tseng
CPC classification number: H04L51/12 , G06F11/00 , G06F15/16 , G06N5/02 , G06N7/00 , G06N7/005 , G06Q50/20
Abstract: Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.
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公开(公告)号:US10523610B2
公开(公告)日:2019-12-31
申请号:US15973130
申请日:2018-05-07
Applicant: Oath Inc.
Inventor: Wei Chu , Martin Zinkevich , Lihong Li , Achint Oommen Thomas , Belle Tseng
Abstract: Software for online active learning receives content posted to an online stream at a website. The software converts the content into an elemental representation and inputs the elemental representation into a probit model to obtain a predictive probability that the content is abusive. The software also calculates an importance weight based on the elemental representation. And the software updates the probit model using the content, the importance weight, and an acquired label if a condition is met. The condition depends on an instrumental distribution. The software removes the content from the online stream if a condition is met. The condition depends on the predictive probability, if an acquired label is unavailable.
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