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    LEARNING REPRESENTATIONS FROM DISPARATE DATA SETS
    3.
    发明申请
    LEARNING REPRESENTATIONS FROM DISPARATE DATA SETS 审中-公开

    公开(公告)号：US20190005409A1

    公开(公告)日：2019-01-03

    申请号：US15639885

    申请日：2017-06-30

    Applicant: Facebook, Inc.

    Inventor： Harsh Doshi ,  Kai Ren ,  Sagar Chordia

    IPC: G06N99/00 ,  G06N5/04

    Abstract: Methods and systems are described herein for jointly training embeddings. The method involves identifying a first data set describing occurrences of a first event type and identifying a second data set describing occurrences of a second event type, in which the first data set and the second data set include a set of users in common. The method further involves jointly training a set of embeddings a joint set of users, involving training the set of users in common based on co-occurrences of events of the first event type first data set and co-occurrences of events of the second event type in the second data set. The method further involves training a computer model that predicts the likelihood of occurrence of a future event for a user with respect to a content item based on the embedding for the user in the jointly trained set of embeddings.

    PREDICTING LATENT METRICS ABOUT USER INTERACTIONS WITH CONTENT BASED ON COMBINATION OF PREDICTED USER INTERACTIONS WITH THE CONTENT
    4.
    发明申请
    PREDICTING LATENT METRICS ABOUT USER INTERACTIONS WITH CONTENT BASED ON COMBINATION OF PREDICTED USER INTERACTIONS WITH THE CONTENT 审中-公开

    公开(公告)号：US20170352109A1

    公开(公告)日：2017-12-07

    申请号：US15174865

    申请日：2016-06-06

    Applicant: Facebook, Inc.

    Inventor： Robert Oliver Burns Zeldin ,  Nathan John Davis ,  Anand Sumatilal Bhalgat ,  Harsh Doshi ,  Hao Song

    IPC: G06Q50/00 ,  G06Q30/08

    CPC classification number: G06Q50/01 ,  G06Q30/08

    Abstract: An online system presenting content items to a user generates a model that predicts a latent metric describing user actions that occur at least a reasonable amount of time after presentation of content items. To determine the latent metric, the online system retrieves one or more models predicting likelihoods of the user performing various interactions when presented with the content items and determines weights associated with different retrieved models. Combining the weighted retrieved models generates a model for determining the latent metric. As the retrieved models are based on data accessible to the online system in less than the reasonable amount of time after presenting content items, weighing the retrieved models allows the online system to predict the latent metric describing user actions occurring after content items are presented. When selecting content items for the user, the online system accounts for the latent metric determined by the generated model.

    Optimization of feature embeddings for deep learning models
    5.
    发明授权
    Optimization of feature embeddings for deep learning models 有权

    公开(公告)号：US11200284B1

    公开(公告)日：2021-12-14

    申请号：US15967414

    申请日：2018-04-30

    Applicant: Facebook, Inc.

    Inventor： Miao Li ,  Sagar Chordia ,  Harsh Doshi ,  Xianjie Chen ,  Qin Huang

    IPC: G06F16/00 ,  G06F16/904 ,  G06N3/04 ,  G06K9/62 ,  G06F16/901

    Abstract: A system trains models to generate embeddings that represent likelihoods associated with features. For example, an embedding may be generated for users and pages such that a user's embedding represents how likely a user is to comment on a given page. Initially, memory space for storing each embedding may be overprovisioned. The system monitors the embeddings for a feature as they are generated and recalculated over time. If the system detects that a particular index value is never updated for embeddings of that feature, then the system may remove that value from the feature embeddings. This allows the array lengths of embeddings to be customized to the particular features they represent, saving memory space. The system may further use related information to identify pooling functions that are most effective for particular features, to identify similarities between entities, and to provide insight into how the feature data influences neural network layers.

    Predicting latent metrics about user interactions with content based on combination of predicted user interactions with the content
    6.
    发明授权
    Predicting latent metrics about user interactions with content based on combination of predicted user interactions with the content 有权

    公开(公告)号：US11094021B2

    公开(公告)日：2021-08-17

    申请号：US15174865

    申请日：2016-06-06

    Applicant: Facebook, Inc.

    Inventor： Robert Oliver Burns Zeldin ,  Nathan John Davis ,  Anand Sumatilal Bhalgat ,  Harsh Doshi ,  Hao Song

    IPC: G06Q50/00 ,  G06Q30/08

    Abstract: An online system presenting content items to a user generates a model that predicts a latent metric describing user actions that occur at least a reasonable amount of time after presentation of content items. To determine the latent metric, the online system retrieves one or more models predicting likelihoods of the user performing various interactions when presented with the content items and determines weights associated with different retrieved models. Combining the weighted retrieved models generates a model for determining the latent metric. As the retrieved models are based on data accessible to the online system in less than the reasonable amount of time after presenting content items, weighing the retrieved models allows the online system to predict the latent metric describing user actions occurring after content items are presented. When selecting content items for the user, the online system accounts for the latent metric determined by the generated model.

    Modifying advertisement bids using predicted advertisement performance
    7.
    发明授权
    Modifying advertisement bids using predicted advertisement performance 有权

    公开(公告)号：US10740789B2

    公开(公告)日：2020-08-11

    申请号：US14965497

    申请日：2015-12-10

    Applicant: Facebook, Inc.

    Inventor： David Paul Capel ,  Harsh Doshi ,  Benjamin Casey Roberts

    IPC: G06Q30/02

    Abstract: An advertising system provides advertisements to client devices. To select advertisements, the advertising system identifies previously selected advertisements to determine which presentations of the advertisement are still in-flight and have not yet resulted in conversion event. The advertising system predicts total advertising spend based on the in-flight advertisements, and adjusts a paced bid for the advertisement by determining whether the estimated total advertising spend, reflecting predicted in-flight advertisements, is above or below an expected spending to reach a budget for the advertising campaign, which may increase or decrease the paced bid.

    OPTIMIZING GENERATION OF A FEED OF CONTENT FOR A USER BASED ON PRIOR USER INTERACTIONS WITH THE FEED OF CONTENT
    8.
    发明申请
    OPTIMIZING GENERATION OF A FEED OF CONTENT FOR A USER BASED ON PRIOR USER INTERACTIONS WITH THE FEED OF CONTENT 审中-公开

    公开(公告)号：US20190139096A1

    公开(公告)日：2019-05-09

    申请号：US15806704

    申请日：2017-11-08

    Applicant: Facebook, Inc.

    Inventor： Zeyue Chen ,  Tanmoy Chakraborty ,  Sergey Markov ,  Harsh Doshi ,  Wei Wei

    IPC: G06Q30/02 ,  G06Q50/00

    Abstract: An online system provides a feed of content including organic content items and sponsored content items that are positioned relative to each other to maximize user interaction with the feed of content. To reduce latency of providing the feed of content to a user without impairing positioning of organic content items and sponsored content items relative to each other, the online system generates the feed of content including organic content items and sends the feed of content to a client device while selecting sponsored content items for the feed of content. The online system transmits selected sponsored content items to the client device, which modifies the feed of content to include the sponsored content items and presents the modified feed of content.

    MODIFYING ADVERTISEMENT BIDS USING PREDICTED ADVERTISEMENT PERFORMANCE
    10.
    发明申请
    MODIFYING ADVERTISEMENT BIDS USING PREDICTED ADVERTISEMENT PERFORMANCE 审中-公开

    公开(公告)号：US20170169465A1

    公开(公告)日：2017-06-15

    申请号：US14965497

    申请日：2015-12-10

    Applicant: Facebook, Inc.

    Inventor： David Paul Capel ,  Harsh Doshi ,  Benjamin Casey Roberts

    IPC: G06Q30/02

    Abstract: An advertising system provides advertisements to client devices. To select advertisements, the advertising system identifies previously selected advertisements to determine which presentations of the advertisement are still in-flight and have not yet resulted in conversion event. The advertising system predicts total advertising spend based on the in-flight advertisements, and adjusts a paced bid for the advertisement by determining whether the estimated total advertising spend, reflecting predicted in-flight advertisements, is above or below an expected spending to reach a budget for the advertising campaign, which may increase or decrease the paced bid.

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