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    Automated Keyword Generation Based on Similarity Score
    1.
    发明申请
    Automated Keyword Generation Based on Similarity Score 有权

    公开(公告)号：US20250110962A1

    公开(公告)日：2025-04-03

    申请号：US18774775

    申请日：2024-07-16

    Applicant: Google LLC

    Inventor： Abhinav Khandelwal ,  Aravindan Raghuveer ,  Snehal Sunilkumar Motarwar ,  Rishi Saket

    IPC: G06F16/2457 ,  G06F16/9538

    Abstract: Methods, computing systems, and technology for generating keywords using machine-learned techniques. The system can receive, from a user device, a first keyword associated with a content item of a first content provider. Additionally, the system can access from a keyword database, a plurality of keywords. Moreover, the system can select, using the machine-learned model, a subset of keywords from the plurality of keywords based on the content item. Furthermore, the system can process, using a machine-learned model, the first keyword and a subset of keywords to calculate a similarity score for each keyword in the subset of keywords and the first keyword. The system can determine a suggested keyword from the subset of keywords based on the similarity score for each keyword in the subset of keywords and the first keyword. Subsequently, the system can cause, on a display of the user device, a presentation of the suggested keyword.

    Generalized Bags for Learning from Label Proportions
    2.
    发明公开
    Generalized Bags for Learning from Label Proportions 审中-公开

    公开(公告)号：US20240119295A1

    公开(公告)日：2024-04-11

    申请号：US18013053

    申请日：2022-01-07

    Applicant: Google LLC

    Inventor： Rishi Saket ,  Aravindan Raghuveer ,  Balaraman Ravindran

    IPC: G06N3/09

    CPC classification number: G06N3/09

    Abstract: Example aspects of the present disclosure relate to an example method. The example method includes obtaining, by a computing system comprising one or more processors, a plurality of data bags. In the example method, each respective data bag of the plurality of data bags comprises a respective plurality of instances and is respectively associated with one or more proportion labels. The example method also includes generating, by the computing system, a plurality of training bags from the plurality of data bags according to a plurality of weights. In the example method, the training bags are generated such that a bag-level predicted proportion label error by a machine-learned prediction model over the plurality of training bags correlates to an instance-level predicted proportion label error by the machine-learned prediction model.

    Automated Content Presentation Based on a Determined Keyword
    4.
    发明申请
    Automated Content Presentation Based on a Determined Keyword 有权

    公开(公告)号：US20250110978A1

    公开(公告)日：2025-04-03

    申请号：US18785949

    申请日：2024-07-26

    Applicant: Google LLC

    Inventor： Abhinav Khandelwal ,  Manoj Kumar Sure ,  Aravindan Raghuveer ,  Saachi Grover ,  Snehal Sunilkumar Motarwar ,  Rishi Saket

    IPC: G06F16/33 ,  G06F16/35 ,  G06Q30/0241

    Abstract: Methods, computing systems, and technology for using machine-learned techniques for determining a keyword for a web resource, and automating content presentation for the web resource. The system can receive, from a user device of a first content provider, a request associated with a web resource having a plurality of assets. Additionally, the system can determine, based on the plurality of assets, a first keyword associated with the web resource. Moreover, the system can determine, based on a first keyword cluster associated with the first keyword, the first keyword being associated with a first query cluster having a query performance metric. Furthermore, the system can process, using a machine-learned forecasting model, the first keyword and the first query cluster to generate a keyword performance metric for the first keyword. Subsequently, the system can perform an action based on the keyword performance metric associated with the first keyword.

    SYSTEMS AND METHODS FOR GENERATING LOCALE-SPECIFIC PHONETIC SPELLING VARIATIONS
    7.
    发明申请
    SYSTEMS AND METHODS FOR GENERATING LOCALE-SPECIFIC PHONETIC SPELLING VARIATIONS 有权

    公开(公告)号：US20220391588A1

    公开(公告)日：2022-12-08

    申请号：US17716430

    申请日：2022-04-08

    Applicant: GOOGLE LLC

    Inventor： Abhirut Gupta ,  Aravindan Raghuveer ,  Abhay Sharma ,  Nitin Raut ,  Manish Kumar

    IPC: G06F40/284 ,  G06F40/232 ,  G06F40/242

    Abstract: Systems and methods for generating phonetic spelling variations of a given word based on locale-specific pronunciations. A phoneme-letter density model may be configured to identify a phoneme sequence corresponding to an input word, and to identify all character sequences that may correspond to an input phoneme sequence and their respective probabilities. The phoneme-phoneme error model may be configured to identify locale-specific alternative phoneme sequences that may correspond to a given phoneme sequence, and their respective probabilities. Using these two models, a processing system may be configured to generate, for a given input word, a list of alternative character sequences that may correspond to the input word based on locale-specific pronunciations, and/or a probability distribution representing how likely each alternative character sequence is to correspond to the input word.

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