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.

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.

公开(公告)号：US20250061312A1

公开(公告)日：2025-02-20

申请号：US18764501

申请日：2024-07-05

Applicant: Google LLC

Inventor： Matthias Heiler ,  Sylvanus Garnet Bent, III ,  Mehmet Levent Koc ,  Snehal Sunilkumar Motarwar ,  Aravindan Raghuveer ,  Saachi Grover ,  Nidhi Gupta ,  Preksha Nema ,  Durga Deepthi Singh Sharma ,  Abhinav Khandelwal

IPC: G06N3/0475

Abstract: Example aspects of the present disclosure provide an example method. In some implementations, the example method can include receiving request data indicating a request for content. In some implementations, the example method can include determining a request context associated with the request data, wherein the request context is based on account data for a user device associated with the request. In some implementations, the example method can include determining, based on the request and the request context, a data object from a knowledge graph, wherein the data object comprises a subject and one or more attributes for the subject. In some implementations, the example method can include generating, using a machine-learned content generation model, content descriptive of the subject, the content generated based on the request, the request context, and the data object.