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公开(公告)号：US10298526B2
公开(公告)日：2019-05-21
申请号：US15263238
申请日：2016-09-12
Applicant: OATH INC.
Inventor： Sharat Narayan , Vishwanath Tumkur Ramarao , Belle Tseng , Markus Weimer , Young Maeng , Jyh-Shin Shue
Abstract: Embodiments are directed towards multi-level entity classification. An object associated with an entity is received. In one embodiment the object comprises and email and the entity comprises the IP address of a sending email server. If the entity has already been classified, as indicated by an entity classification cache, then a corresponding action is taken on the object. However, if the entity has not been classified, the entity is submitted to a fast classifier for classification. A feature collector concurrently fetches available features, including fast features and full features. The fast classifier classifies the entity based on the fast features, storing the result in the entity classification cache. Subsequent objects associated with the entity are processed based on the cached result of the fast classifier. Then, a full classifier classifies the entity based on at least the full features, storing the result in the entity classification cache.
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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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