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公开(公告)号：US10412032B2
公开(公告)日：2019-09-10
申请号：US15642579
申请日：2017-07-06
Applicant: Facebook, Inc.
Inventor： Emanuel Alexandre Strauss , Muhammad Saif Farooqui , Rehman Mehdi Muhammad , Michelle Ruby Hwang , Nicolas Scheffer , Joseph Rhyu
Abstract: Techniques for scam detection and prevention are described. In one embodiment, an apparatus may comprise an interaction processing component operative to generate a scam message example repository; submit the scam message example repository to a natural-language machine learning component; and receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; an interaction monitoring component operative to monitor a plurality of messaging interactions with a messaging system based on the scam message model; and determine a suspected scam messaging interaction of the plurality of messaging interactions; and a scam action component operative to perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. Other embodiments are described and claimed.
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2.发明申请RANKING OF SPONSORED CONTENT ITEMS FOR COMPLIANCE WITH POLICIES ENFORCED BY AN ONLINE SYSTEM 审中-公开赞助内容项目符合在线系统实施的政策公开(公告)号：US20170068964A1
公开(公告)日：2017-03-09
申请号：US14849557
申请日：2015-09-09
Applicant: Facebook, Inc.
Inventor： Igor Gevka , Hongda Ma , Satwik Shukla , Yufei Chen , Daniel Tam , Emanuel Alexandre Strauss , Daniel Olmedilla de la Calle , Sarang Mohan Joshi
CPC classification number: G06Q30/018 , G06Q30/0273 , G06Q30/0277
Abstract: An online system receives advertisements from advertisers and reviews the advertisement for compliance with policies enforced by the online system. The online system computes scores for each advertisement based on an expected revenue from presenting various advertisement and/or interactions with various advertisements and orders advertisements for review based on their scores. If a predicted time for the online system to review an advertisement is greater than a threshold amount of time, the online system allows the online system to be evaluated for presentation to users. As the online system receives interactions with the advertisement, the online system may modify the score for the advertisement and modify the order of the advertisement for review based on the modified score.
Abstract translation: 在线系统接收来自广告客户的广告，并对广告进行审查，以符合在线系统执行的政策。 在线系统基于通过各种广告呈现各种广告和/或交互的预期收入以及基于他们的分数来审查的订单广告来计算每个广告的分数。 如果在线系统审查广告的预测时间大于阈值时间，则在线系统允许评估在线系统以呈现给用户。 随着在线系统接收到广告的互动，在线系统可以修改广告的分数，并根据修改的分数修改广告的顺序进行审核。
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公开(公告)号：US11283743B1
公开(公告)日：2022-03-22
申请号：US16519685
申请日：2019-07-23
Applicant: Facebook, Inc.
Inventor： Emanuel Alexandre Strauss , Muhammad Saif Farooqui , Rehman Mehdi Muhammad , Michelle Ruby Hwang , Nicolas Scheffer
Abstract: Techniques for scam detection and prevention are described. In one embodiment, an apparatus may comprise an interaction processing component operative to generate a scam message example repository; submit the scam message example repository to a natural-language machine learning component; and receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; an interaction monitoring component operative to monitor a plurality of messaging interactions with a messaging system based on the scam message model; and determine a suspected scam messaging interaction of the plurality of messaging interactions; and a scam action component operative to perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. Other embodiments are described and claimed.
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公开(公告)号：US11023823B2
公开(公告)日：2021-06-01
申请号：US15449448
申请日：2017-03-03
Applicant: Facebook, Inc.
Inventor： Emanuel Alexandre Strauss
Abstract: An online system maintains machine learning models that determine risk scores for content items indicating likelihoods of content items violating content policies associated with the machine learning models. When the online system obtains an additional content policy, the online system applies a maintained machine learning model to a set including content items previously identified as violating or not violating the additional content policy. The online system maps the risk scores determined for content items of the set to likelihoods of violating the additional content policy based on the identifications of content times in the set violating or not violating the additional content policy. Subsequently, the online system applies the maintained machine learning model to content items and determines likelihoods of the content items violating the additional content policy based on the mapping of risk scores to likelihood of violating the additional content policy.
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5.发明申请公开(公告)号：US20190073592A1
公开(公告)日：2019-03-07
申请号：US15694321
申请日：2017-09-01
Applicant: Facebook, Inc.
Inventor： Enming Luo , Yang Mu , Emanuel Alexandre Strauss , Taiyuan Zhang , Daniel Olmedilla de la Calle
Abstract: A content review system for an online system automatically determines if received content items to be displayed to users violate any policies of the online system. The content review system generates a semantic vector representing the semantic features of a content item, for example, using a neural network. By comparing the semantic vector for the content item with semantic vectors of content items previously determined to violate one or more policies, the content review system determines whether the content item also violates one or more policies. The content review system may also maintain templates corresponding to portions of semantic vectors shared by multiple content items. An analysis of historical content items that conform to the template is performed to determine a probability that received content items that conform to the template violate a policy.
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Patent Agency Ranking
公开(公告)号：US10936952B2
公开(公告)日：2021-03-02
申请号：US15694339
申请日：2017-09-01
Applicant: Facebook, Inc.
Inventor： Enming Luo , Yang Mu , Emanuel Alexandre Strauss , Taiyuan Zhang , Daniel Olmedilla de la Calle
Abstract: A content review system for an online system automatically determines if received content items to be displayed to users violate any policies of the online system. The content review system generates a semantic vector representing the semantic features of a content item, for example, using a neural network. By comparing the semantic vector for the content item with semantic vectors of content items previously determined to violate one or more policies, the content review system determines whether the content item also violates one or more policies. The content review system may also maintain templates corresponding to portions of semantic vectors shared by multiple content items. An analysis of historical content items that conform to the template is performed to determine a probability that received content items that conform to the template violate a policy.
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公开(公告)号：US10853431B1
公开(公告)日：2020-12-01
申请号：US15854667
申请日：2017-12-26
Applicant: Facebook, Inc.
IPC: G06F16/9535 , G06N20/00 , G06F16/955 , G06F16/958 , G06F40/117 , G06F16/957 , H04L29/06
Abstract: An online system determines a quality of content provided by third party systems for distribution to users. The online system analyzes URL's posted within the online system by content providers to determine the quality of content of the webpages obtained by accessing the URLs. For each URL, the online system receives an original markup language document and a copy of the markup document obtained by applying a content filter. The online system extracts features from both markup language documents. The online system provides the extracted features to a machine learning based model to generate a content quality score. The online system categorizes the URL as having high quality content or low quality content. The online system restricts distribution of content items including URLs to websites with low quality content.
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公开(公告)号：US20190073593A1
公开(公告)日：2019-03-07
申请号：US15694339
申请日：2017-09-01
Applicant: Facebook, Inc.
Inventor： Enming Luo , Yang Mu , Emanuel Alexandre Strauss , Taiyuan Zhang , Daniel Olmedilla de la Calle
Abstract: A content review system for an online system automatically determines if received content items to be displayed to users violate any policies of the online system. The content review system generates a semantic vector representing the semantic features of a content item, for example, using a neural network. By comparing the semantic vector for the content item with semantic vectors of content items previously determined to violate one or more policies, the content review system determines whether the content item also violates one or more policies. The content review system may also maintain templates corresponding to portions of semantic vectors shared by multiple content items. An analysis of historical content items that conform to the template is performed to determine a probability that received content items that conform to the template violate a policy.
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公开(公告)号：US20190014064A1
公开(公告)日：2019-01-10
申请号：US15642579
申请日：2017-07-06
Applicant: Facebook, Inc.
Inventor： Emanuel Alexandre Strauss , Muhammad Saif Farooqui , Rehman Mehdi Muhammad , Michelle Ruby Hwang , Nicolas Scheffer , Joseph Rhyu
CPC classification number: H04L51/12 , G06N3/0445 , G06N3/0454 , G06N20/00 , G06N99/005 , H04L29/08072 , H04L51/32 , H04L63/1408 , H04L63/1441
Abstract: Techniques for scam detection and prevention are described. In one embodiment, an apparatus may comprise an interaction processing component operative to generate a scam message example repository; submit the scam message example repository to a natural-language machine learning component; and receive a scam message model from the natural-language machine learning component in response to submitting the scam message example repository; an interaction monitoring component operative to monitor a plurality of messaging interactions with a messaging system based on the scam message model; and determine a suspected scam messaging interaction of the plurality of messaging interactions; and a scam action component operative to perform a suspected scam messaging action with the messaging system in response to determining the suspected scam messaging interaction. Other embodiments are described and claimed.
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公开(公告)号：US10853838B2
公开(公告)日：2020-12-01
申请号：US15608803
申请日：2017-05-30
Applicant: Facebook, Inc.
Inventor： Yang Mu , Emanuel Alexandre Strauss , Daniel Olmedilla de la Calle
Abstract: For various content campaigns (or content), an online system predicts a likelihood score of context violations (e.g., account term violations) of a content campaign. The online system derives a plurality of feature vectors of the content campaign. The online system predicts a likelihood score of context violation of the content campaign using a memorization model based on the plurality of feature vectors. The memorization model comprises a plurality of categories and a plurality of items of each category. Each of the plurality of categories has a category weight, and each of the plurality of items of each category has an item weight. The predicted likelihood score is based on a combination of a plurality of category weights and a plurality of item weights associated with the plurality of feature vectors. The online system performs an action affecting the content campaign based in part on the predicted likelihood score.
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