Granular Cluster Generation for Real-Time Processing

    公开(公告)号:US20230267176A1

    公开(公告)日:2023-08-24

    申请号:US18167297

    申请日:2023-02-10

    Applicant: Google LLC

    CPC classification number: G06F18/23211 G06F16/906 G06F16/215 G06F18/23213

    Abstract: Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

    Granular cluster generation for real-time processing

    公开(公告)号:US12086211B2

    公开(公告)日:2024-09-10

    申请号:US18167297

    申请日:2023-02-10

    Applicant: Google LLC

    CPC classification number: G06F18/23211 G06F16/215 G06F16/906 G06F18/23213

    Abstract: Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

    Mixing of Media Content Items for Display on a Focus Area of A Network-Connected Television Device

    公开(公告)号:US20210289261A1

    公开(公告)日:2021-09-16

    申请号:US16919931

    申请日:2020-07-02

    Applicant: Google LLC

    Abstract: This application is directed to presenting a unified user interface on a network-connected television device. The unified user interface displays media content recommendations selected and organized based on knowledge of a user (e.g., search queries, search results, watch history, purchase history, physical activities). The unified user interface also includes a focus area for displaying a series of media content items (e.g., an advertisement) sequentially according to a temporal order for the purposes of promoting a media content item, product, event or service. In some implementations, playback of a media content item presented on the unified user interface relies on a collaborative implementation of a corresponding media player application and a media content casting application, particularly when the play involves a restricted mode. The content casting application is enabled to play the media content item at the restrict mode when the media player application does not operate in the restricted mode.

    Machine learning based automatic audience segment in ad targeting

    公开(公告)号:US11580170B2

    公开(公告)日:2023-02-14

    申请号:US16670809

    申请日:2019-10-31

    Applicant: Google LLC

    Abstract: Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

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