IMAGE BASED PREDICTION OF USER DEMOGRAPHICS
    11.
    发明申请

    公开(公告)号:US20180314915A1

    公开(公告)日:2018-11-01

    申请号:US15497866

    申请日:2017-04-26

    Applicant: Facebook, Inc.

    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.

    DEMOGRAPHIC PREDICTION FOR USERS IN AN ONLINE SYSTEM WITH UNIDIRECTIONAL CONNECTION

    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.

    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.

    ESTIMATION OF REACH OVERLAP AND UNIQUE REACH FOR DELIVERY OF CONTENT ITEMS

    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.

    CPC classification number: G06N20/00 H04L67/22

    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.

    Determining performance metrics for delivery of electronic media content items by online publishers

    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.

    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.

    DETERMINING PERFORMANCE METRICS FOR DELIVERY OF ELECTRONIC MEDIA CONTENT ITEMS BY ONLINE PUBLISHERS

    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.

    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.

    Image based prediction of user demographics

    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.

    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.

    GENERATING MODELS TO MEASURE PERFORMANCE OF CONTENT PRESENTED TO A PLURALITY OF IDENTIFIABLE AND NON-IDENTIFIABLE INDIVIDUALS

    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.

    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.

    DEMOGRAPHIC PREDICTION FOR UNRESOLVED USERS
    19.
    发明申请

    公开(公告)号:US20180204230A1

    公开(公告)日:2018-07-19

    申请号:US15408121

    申请日:2017-01-17

    Applicant: Facebook, Inc.

    Abstract: Disclosed is an online system that infers demographic attributes of unresolved users for whom the demographic attributes are not known. The online system determines certain features about devices used by the unresolved users, but does not have certain information about the users themselves (e.g., their age, gender, or location), so instead infers these attributes based on the features of the user devices. The online system provides the features about the devices as input to a classifier trained to predict a particular demographic attribute value, and the classifier outputs a prediction of whether the user of the user device has the corresponding value of the demographic attribute. In one embodiment, the online system trains a classifier for various demographic attribute values by forming training sets for the demographic attribute values using the features of devices for users who are logged into the online system and hence have known demographic attribute values.

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