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公开(公告)号：US11182863B1
公开(公告)日：2021-11-23
申请号：US16362222
申请日：2019-03-22
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke , Gunjit Singh
IPC: G06F16/9535 , G06Q50/00
Abstract: An online system generates content feature entries, with each content feature entry describing a content item from a third party system. The online system generates user feature entries, each user feature entry describing a user. The online system generates a combination score for a target user and a selected content item by computing a combination of the content feature entries associated with the selected content item and the user feature entries associated with the target user using a combining function. The combination score indicates an estimated increase in value for the third party system when the target user is presented with the selected content item. The online system selects content items to transmit to a client device of a target user of the online system for presentation to the target user based on the combination score for the content items and the target user.
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公开(公告)号：US20190050892A1
公开(公告)日：2019-02-14
申请号：US15676928
申请日：2017-08-14
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke
IPC: G06Q30/02
CPC classification number: G06Q30/0244 , G06Q30/0275 , G06Q30/0277
Abstract: An online system determines how presenting an awareness campaign to a user will affect the user's likelihood of converting to a related direct response campaign. For the user, the online system creates a benchmark exposure profile representing the user's exposure history before the awareness campaign. Similarly, the online system determines the user's simulated exposure profile, which represents the user's brand exposure history after having been exposed to the awareness campaign. A response prediction for the direct response campaign is determined for the benchmark exposure profile and the simulated exposure profile. The online system estimates the difference between the response prediction and the simulated response prediction to determine a delivery control value of presenting the awareness campaign to a user. The delivery control value is used to determine an effective impression value for the awareness campaign and conversion value for the related direct response campaign.
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公开(公告)号：US20180260736A1
公开(公告)日：2018-09-13
申请号：US15455051
申请日：2017-03-09
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke , Gunjit Singh
Abstract: When an opportunity arises to present a content item to a user, an online system delivers a content item to a user according to a first content delivery strategy associated with the content item. For the impression of the content item to the user, the online system tracks attributes associated with the first content delivery strategy. In addition to tracking the attributes associated with the first content delivery strategy, the online system also tracks attributes associated with at least one other content delivery strategy (a second content delivery strategy). The attributes tracked for the second content delivery strategy are used to train a machine learning model for the second content delivery strategy. The model is used to deliver the content item or other items according to the second content delivery strategy.
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公开(公告)号：US20190102694A1
公开(公告)日：2019-04-04
申请号：US15721203
申请日：2017-09-29
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Gunjit Singh , Kurt Dodge Runke
Abstract: An online system uses multiple machine learning models to select content for providing to a user of the online system. Specifically, the online system trains a general model that intakes a first set of features and outputs predictions at a general level. The online system further trains a residual model that intakes a second set of features. The residual model predicts a residual (e.g., an error) of the predictions outputted by the general model. Therefore, the predicted residual from the residual model is combined with the prediction from the general model in order to correct for the over-generality of the general model. The online system may use the combined prediction to send content to users.
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5.发明申请公开(公告)号：US20180150572A1
公开(公告)日：2018-05-31
申请号：US15365899
申请日：2016-11-30
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke , Gunjit Singh
CPC classification number: G06Q50/01 , G06F17/30867
Abstract: An online system receives third party source data from a third party system including content feature vector entries and user feature vector entries, each content feature vector entry describing an corresponding user of the third party system, each component in each user feature vector related to a characteristic of the corresponding user. The online system generates a combination score for a target user and a selected content item by computing a combination of the content feature vector entry associated with the selected content item and the user feature vector entry associated with the target user using a combining function, the combination score indicating an estimated increase in value for the third party system when the target user is presented with the selected content item.
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Patent Agency Ranking
公开(公告)号：US10282792B2
公开(公告)日：2019-05-07
申请号：US15365899
申请日：2016-11-30
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke , Gunjit Singh
Abstract: An online system receives third party source data from a third party system including content feature vector entries and user feature vector entries, each content feature vector entry describing an corresponding user of the third party system, each component in each user feature vector related to a characteristic of the corresponding user. The online system generates a combination score for a target user and a selected content item by computing a combination of the content feature vector entry associated with the selected content item and the user feature vector entry associated with the target user using a combining function, the combination score indicating an estimated increase in value for the third party system when the target user is presented with the selected content item.
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公开(公告)号：US20180268303A1
公开(公告)日：2018-09-20
申请号：US15462896
申请日：2017-03-19
Applicant: Facebook, Inc.
Inventor： Ramnik Arora , Kurt Dodge Runke
CPC classification number: G06F16/9535 , G06F7/58 , G06F16/958 , G06F17/5009 , G06F2217/04 , G06N7/005 , G06Q30/02 , G06Q30/0241 , G06Q30/0251 , G06Q30/0269 , G06Q30/0277 , G06Q50/01
Abstract: An online system generates, based on previously recorded content presentations, user value distributions for users of the online system. The online system also receives third party specifications from a third party system. Using this information, the online system generates a simulation for presenting content to users of the online system based on the third party specifications. For each iteration of the simulation, the online system randomly selects a user of the online system matching specifications, accesses the user value distribution for the randomly selected user, computes a selection probability of a successful content presentation to the randomly selected user, and simulates a content transmission based on the selection probability. The results of the simulation are reported to the third party system.
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公开(公告)号：US20180197090A1
公开(公告)日：2018-07-12
申请号：US15403093
申请日：2017-01-10
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Kurt Dodge Runke , Gunjit Singh
IPC: G06N5/04
CPC classification number: G06N3/04 , G06Q30/02 , G06Q30/0241 , G06Q50/01
Abstract: An online system receives explicit user data and explicit event data, and implicit user data and implicit event data from a third party system. The online system generates an implicit users/implicit events data feature, an explicit users/explicit events data feature, and an explicit users/implicit events data feature. The online system generates a prediction of the counterfactual rate based on the implicit users/implicit events data feature, the explicit users/explicit events data feature, and the explicit users/explicit events data feature, the counterfactual rate indicating the likelihood that target users matching certain characteristics caused an event to occur when the target are not been presented with content by the online system, the content configured to induce users to cause the event to occur. A combined prediction rate is presented to the third party system based on the counterfactual rate.
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公开(公告)号：US20180025389A1
公开(公告)日：2018-01-25
申请号：US15216529
申请日：2016-07-21
Applicant: Facebook, Inc.
Inventor： Ramnik Arora , Kurt Dodge Runke
CPC classification number: G06Q30/0275 , G06Q30/0244 , H04L67/306 , H04W4/23
Abstract: An online system determines an advertiser value curve specific to a content item that may be presented to a viewing user of the online system, where points along the advertiser value curve represent values of potential impressions that may be obtained for the content item, which decreases as the number of potential impressions increases. The online system also determines a user cost curve specific to the viewing user, where points along the user cost curve represent costs of previous impressions of one or more content items obtained for the viewing user, which increases as the number of impressions of the content items increases. An efficient bid amount for each impression opportunity for the viewing user to view the content item is determined based on a number of total impressions and a bid amount that are associated with an intersection of the curves.
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公开(公告)号：US10936954B2
公开(公告)日：2021-03-02
申请号：US15447068
申请日：2017-03-01
Applicant: Facebook, Inc.
Inventor： Andrew Donald Yates , Gunjit Singh , Kurt Dodge Runke
Abstract: An online system generates predicted outcomes for a content distribution program that distributes content to users of the online system, the predicted outcome indicating a likelihood for the occurrence of an outcome of a content presentation. The online system transmits the one or more predicted outcomes to the third party system, and receives prediction improvement data from the third party system, the prediction improvement data indicating an adjustment to errors in the predicted outcomes based on a prediction by the third party system. The online system updates the properties of a content distribution program based on the prediction improvement data, the updated content distribution program causing the online system to generate new predicted outcomes based on the prediction improvement data in content presentation opportunities. The online system also transmits content to users of the online system based on the updated content distribution program.
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