Online active learning in user-generated content streams

    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.

    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.

    Online active learning in user-generated content streams

    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.

    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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