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公开(公告)号：US20180204133A1
公开(公告)日：2018-07-19
申请号：US15409374
申请日：2017-01-18
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Goran Predovic
CPC classification number: G06N20/00 , G06F16/335 , H04L67/18 , H04L67/306
Abstract: Disclosed is a content sharing system that infers demographic attributes of users of the content sharing system based on features of the users with accounts matched to an online system with known demographic attributes. The features include attributes of unidirectional connections of the users on the content sharing system. In some embodiments, the features are distributions of demographic attributes of the unidirectional connections of the users, such as distributions of ages or genders of the unidirectional connections. The content sharing system provides the features as input to a classifier trained to predict a particular demographic attribute value and the classifier outputs a predicted value of that demographic attribute. In some embodiments, the content sharing system trains a classifier for various demographic attributes by forming training sets for the demographic attributes using the features for users.
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公开(公告)号：US20180060753A1
公开(公告)日：2018-03-01
申请号：US15250452
申请日：2016-08-29
Applicant: Facebook, Inc.
Inventor： Liang Xu , Chaochao Cai , Goran Predovic
Abstract: An online system obtains a set of resolved impressions based on historical data about multiple publishers. A set of features is then extracted, for each resolved impression, based on a comparison of historical data about the first publisher and the second publisher. The online system performs training of a machine-learned model based on the set of features. Data about a plurality of new impressions are input into the trained machine-learned model to obtain an output of the trained machine-learned model. A reach overlap metric and unique reach metric can be computed based on the output of the trained machine-learned model.
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公开(公告)号：US10922335B1
公开(公告)日：2021-02-16
申请号：US15883036
申请日：2018-01-29
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Goran Predovic , Liang Xu , Qing Li , Logan Michael Gore
Abstract: A method for providing content items to one or more client devices associated with at least one unresolved identifier. An unresolved identifier defines a context in which a client device accesses one or more online systems, the context not determined to be associated with a specific user. The method comprises identifying a set of unresolved identifiers, and identifying information describing one or more access events associated with each unresolved identifier. For each pair of unresolved identifiers, a similarity score for the pair is determined based on the identified information. Responsive to the similarity score exceeding a threshold similarity score, the pair of unresolved identifiers is clustered, the clustering indicating a prediction that the pair of unresolved identifiers are associated with a common user. Based on this clustering, a content item is displayed on or more user devices associated with at least one unresolved identifier of the set of unresolved identifiers.
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公开(公告)号：US10387715B1
公开(公告)日：2019-08-20
申请号：US16201852
申请日：2018-11-27
Applicant: Facebook, Inc.
Inventor： Aleksey Sergeyevich Fadeev , Li Zhou , Yimin Song , Goran Predovic , Chaochao Cai , Liang Xu
Abstract: An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.
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15.发明申请公开(公告)号：US20170093650A1
公开(公告)日：2017-03-30
申请号：US14866059
申请日：2015-09-25
Applicant: Facebook, Inc.
Inventor： Goran Predovic , Liang Xu , Stephane Taine
CPC classification number: H04L67/02 , H04L12/1475 , H04L12/1496 , H04L67/22 , H04L67/306 , H04M15/00 , H04M15/07 , H04M15/09 , H04M15/64 , H04M15/8083
Abstract: An online system determines one or more metrics describing consumption of content by various users by identifying users of the online system capable of being identified based on information received from multiple client devices. For example, the online system identifies users associated with user identifiers that are also associated with other types of identifying information (e.g., cookies, device identifiers). From the identified users, the online system generates a set of users based on a distribution of characteristics. The distribution of characteristics may be determined by the online system as characteristics of a group of users or received by the online system from a third party system and describes characteristics of users of the third party system. Based on interactions with content by users in the set, the online system determines one or more metrics describing consumption of content.
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Patent Agency Ranking
16.发明授权公开(公告)号：US11238490B2
公开(公告)日：2022-02-01
申请号：US15792641
申请日：2017-10-24
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Liang Xu , Goran Predovic
Abstract: Information describing deliveries of content items and user actions associated with the content items is stored. Each delivery is performed by an online publisher to a user. A user action associated with a content item performed by a target user is detected. Information describing a set of online publishers that delivered the content item to the target user is retrieved. For each online publisher of the set, a likelihood that the user action would have occurred without the online publisher's delivery of the content item to the target user is determined. An estimated increase in the likelihood that the user action occurred due to the online publisher's delivery of the content item to the target user is determined. A performance metric is determined for the online publisher, wherein ratios of performance metrics for the set of online publishers are related based on corresponding ratios of the estimated increases in likelihoods.
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17.发明申请公开(公告)号：US20190122257A1
公开(公告)日：2019-04-25
申请号：US15792641
申请日：2017-10-24
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Liang Xu , Goran Predovic
Abstract: Information describing deliveries of content items and user actions associated with the content items is stored. Each delivery is performed by an online publisher to a user. A user action associated with a content item performed by a target user is detected. Information describing a set of online publishers that delivered the content item to the target user is retrieved. For each online publisher of the set, a likelihood that the user action would have occurred without the online publisher's delivery of the content item to the target user is determined. An estimated increase in the likelihood that the user action occurred due to the online publisher's delivery of the content item to the target user is determined. A performance metric is determined for the online publisher, wherein ratios of performance metrics for the set of online publishers are related based on corresponding ratios of the estimated increases in likelihoods.
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公开(公告)号：US10210429B2
公开(公告)日：2019-02-19
申请号：US15497866
申请日：2017-04-26
Applicant: Facebook, Inc.
Inventor： Chaochao Cai , Goran Predovic , Wei Wei , Chang Liu , Liang Xu
Abstract: An online system predicts gender, age, interests, or other demographic information of a user based on image data of the user, e.g., profile photos, photos the user posts of him/herself within an online system, and photos of the user posted by other users socially connected with the user, and textual data in the user's profile that suggests age or gender (e.g., like or dislikes similar to a population of users of an online system). The online system similarly predicts a user's interests based on the photos of the user. The online system applies one or more models trained using deep learning techniques to generate the predictions. The online system uses the predictions to build more information about the user in the online system, and provide improved and targeted content delivery to the user that may have disparate information scattered throughout different online systems.
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公开(公告)号：US20180314880A1
公开(公告)日：2018-11-01
申请号：US15497454
申请日：2017-04-26
Applicant: Facebook, Inc.
Inventor： Aleksey Sergeyevich Fadeev , Li Zhou , Yimin Song , Goran Predovic , Chaochao Cai , Liang Xu
CPC classification number: G06K9/00295 , G06F17/27 , G06F17/30867 , G06K9/00275 , G06Q50/01 , H04L51/10 , H04L51/32 , H04L67/306
Abstract: An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.
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20.发明申请公开(公告)号：US20180218286A1
公开(公告)日：2018-08-02
申请号：US15421060
申请日：2017-01-31
Applicant: Facebook, Inc.
Inventor： Goran Predovic , Liang Xu , Chaochao Cai
CPC classification number: G06N20/00 , G06F16/235 , G06F16/2462 , G06F16/95 , G06N5/003 , G06N20/20
Abstract: An online system measures performance of content presented to a plurality of identifiable and non-identifiable individuals based on matching user identifying information included in data describing presentation of the content and data describing performance of an action associated with the content. To reduce measurement inaccuracy resulting from incomplete matching of user identifying information associated with non-identifiable individuals, the online system generates models to extrapolate data describing an amount of unique individuals presented with the content, an amount of unique individuals who performed an action associated with the content, and an amount of unique individuals who performed the action associated with the content attributable to presentation of the content by a content publisher. The models are applied to data collected by the online system describing presentation of the content and performance of actions associated with the content. Metrics describing performance of the content are generated based on the models.
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