LOCALIZATION OF MACHINE LEARNING MODELS TRAINED WITH GLOBAL DATA

    公开(公告)号:US20220207407A1

    公开(公告)日:2022-06-30

    申请号:US17134430

    申请日:2020-12-27

    Abstract: Systems, devices, and techniques are disclosed for localization of machine learning models trained with global data. Data sets of event data for users may be received. The data sets may belong to separate groups. The data sets of event data may be combined to generate a global data set. A matrix factorization model may be trained using the global data set to generate a globally trained matrix factorization model. A localization group data set may be generated including event data from the global data set for users from a first of the groups. The globally trained matrix factorization model may be trained with the localization group data set to generate a localized matrix factorization model for the first of the groups.

    Dynamic ranking of recommendation pairings

    公开(公告)号:US11373232B2

    公开(公告)日:2022-06-28

    申请号:US16421525

    申请日:2019-05-24

    Abstract: A graphical user interface (GUI) may be provided by a computing system that implements a database system for presentation at a client device. The GUI may display a designated one or more criteria for selecting one of a plurality of recommendations for a target object instance associated with a designated object definition. A predictive model for determining a propensity score for selected ones of the plurality of recommendations in association with the target object instance may be configured. The propensity score may be a function of one or more data field values associated with the target object instance and may be configured based on user input received via the graphical user interface. The predictive model may be stored on a storage medium for retrieval when selecting recommendations in response to requests received to access instances of the designated object definition.

    Monitoring resource utilization of an online system based on statistics describing browser attributes

    公开(公告)号:US11368464B2

    公开(公告)日:2022-06-21

    申请号:US16698970

    申请日:2019-11-28

    Abstract: An online system monitors resources utilization by users connecting with the online system and detects unauthorized resource utilization. The online system collects samples of browser attributes from browsers interacting with the online system. The online system determines statistics describing the browser attributes based on the collected samples for that user. The online system receives values of browser attributes for a new request received from a user and determines a browser score indicating a likelihood that the new request was sent from a new client device different from the client devices used by the user during the time interval. If the online system determines that the score indicates that the new request was sent by the new client device, the online system takes mitigating actions to control the unauthorized resource utilization, for example, by requesting credentials for authenticating the request.

    ONLINE RECOMMENDATIONS
    266.
    发明申请

    公开(公告)号:US20220188900A1

    公开(公告)日:2022-06-16

    申请号:US17688159

    申请日:2022-03-07

    Abstract: A group of recommendations related to an item, such as an item of content presented to a user in a page, can be ranked according to a probability distribution that is iteratively updated with each user interaction. For practical implementations, a click stream of interactions may be logged, and then applied in a batch process to update the probability distribution on any suitable schedule independent of the timing of incoming user interactions.

    COMPONENTIZED DASHBOARDS
    267.
    发明申请

    公开(公告)号:US20220188327A1

    公开(公告)日:2022-06-16

    申请号:US17124250

    申请日:2020-12-16

    Abstract: Described herein are systems, apparatus, methods and computer program products configured for componentized dashboards for data visualization. In certain embodiments, a component may be configured to be integrated within a dashboard. The component may receive data from one or more user database and provide one or more representations of the data. The component may be integrated within the dashboard as a separate component. That is, the component may provide the plurality of representations independent of the dashboard. The component may be maintained independent of the dashboard and, thus, may be updated independent of the dashboard.

    Method and a system for fuzzy matching of entities in a database system based on machine learning

    公开(公告)号:US11360990B2

    公开(公告)日:2022-06-14

    申请号:US16449335

    申请日:2019-06-21

    Abstract: A method and system of matching field values of a field type are described. Blurring operations are applied on a first and second values to obtain blurred values. A first maximum score is determined from first scores for blurred values, where each one of the first scores is indicative of a confidence that a match of the first and the second values occurs with knowledge of a first blurred value. A second maximum score is determined from second scores for the blurred values, where each one of the second scores is indicative of a confidence that a non-match of the first and the second values occurs with knowledge of the first blurred value. Responsive to determining that the first maximum score is greater than the second maximum score, an indication that the first value matches the second value is output.

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