中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

39 records (took 0.021 seconds)

    COMPUTING RESOURCE ALLOCATION MECHANISM TESTING AND DEPLOYMENT
    11.
    发明公开
    COMPUTING RESOURCE ALLOCATION MECHANISM TESTING AND DEPLOYMENT 审中-公开

    公开(公告)号：US20240303176A1

    公开(公告)日：2024-09-12

    申请号：US18178715

    申请日：2023-03-06

    Applicant: Adobe Inc.

    Inventor： Raunak Shah ,  Shiv Kumar Saini ,  Atanu R. Sinha

    IPC: G06F11/34 ,  G06F9/50

    CPC classification number: G06F11/3442 ,  G06F9/5077

    Abstract: A computing resource allocation system receives entity resource usage data describing computing resource usage of an executable service platform by an entity as part of a first allocation generated using a first allocation mechanism. A computing resource allocation system generates an entity resource model based on the entity resource usage data of the computing resource usage of the executable service platform as part of the first allocation mechanism. A computing resource allocation system simulates computing resource usage of the executable service platform by the entity as part of a second allocation mechanism based on the entity resource model and the entity resource usage data. A computing resource allocation system estimates a second allocation to provide to the entity based on the simulating.

    Cloud-based resource allocation using meters
    12.
    发明授权
    Cloud-based resource allocation using meters 有权

    公开(公告)号：US12086646B2

    公开(公告)日：2024-09-10

    申请号：US17674578

    申请日：2022-02-17

    Applicant: Adobe Inc.

    Inventor： Atanu R. Sinha ,  Shiv Kumar Saini ,  Sapthotharan Krishnan Nair ,  Saarthak Sandip Marathe ,  Manupriya Gupta ,  Brahmbhatt Paresh Anand ,  Ayush Chauhan

    IPC: G06F3/00 ,  G06F9/50 ,  H04L47/70 ,  H04L67/10

    CPC classification number: G06F9/5055 ,  H04L47/826 ,  H04L67/10

    Abstract: In implementations of systems for cloud-based resource allocation using meters, a computing device implements a resource system to receive resource data describing an amount of cloud-based resources reserved for consumption by client devices during a period of time and a total amount of cloud-based resources consumed by the client devices during the period of time. The resource system determines a consumption distribution using each meter included in a set of meters. Each of the consumption distributions allocates a portion of the total amount of the cloud-based resources consumed to each client device of the client devices. A particular meter used to determine a particular consumption distribution is selected based on a Kendall Tau coefficient of the particular consumption distribution. An amount of cloud-based resources to allocate for a future period of time is estimated using the particular meter and an approximate Shapley value.

    PROVISIONING INTERACTIVE CONTENT BASED ON PREDICTED USER-ENGAGEMENT LEVELS
    15.
    发明申请
    PROVISIONING INTERACTIVE CONTENT BASED ON PREDICTED USER-ENGAGEMENT LEVELS 有权

    公开(公告)号：US20220366299A1

    公开(公告)日：2022-11-17

    申请号：US17322108

    申请日：2021-05-17

    Applicant: Adobe Inc.

    Inventor： Atanu R. Sinha ,  Xiang Chen ,  Sungchul Kim ,  Omar Rahman ,  Jean Bernard Hishamunda ,  Goutham Srivatsav Arra

    IPC: G06N20/00 ,  G06F3/0484 ,  H04L29/08

    Abstract: Methods and systems disclosed herein relate generally to systems and methods for using a machine-learning model to predict user-engagement levels of users in response to presentation of future interactive content. A content provider system accesses a machine-learning model, which was trained using a training dataset including previous user-device actions performed by a plurality of users in response to previous interactive content. The content provider system receives user-activity data of a particular user and applies the machine-learning model to the user-activity data, in which the user-activity data includes user-device actions performed by the particular user in response to interactive content. The machine-learning model generates an output including a categorical value that represents a predicted user-engagement level of the particular user in response to a presentation of the future interactive content.

    Systems for Predicting a Terminal Event
    17.
    发明申请
    Systems for Predicting a Terminal Event 有权

    公开(公告)号：US20210342649A1

    公开(公告)日：2021-11-04

    申请号：US16866261

    申请日：2020-05-04

    Applicant: Adobe Inc.

    Inventor： Amit Doda ,  Gaurav Sinha ,  Kai Yeung Lau ,  Akangsha Sunil Bedmutha ,  Shiv Kumar Saini ,  Ritwik Sinha ,  Vaidyanathan Venkatraman ,  Niranjan Shivanand Kumbi ,  Omar Rahman ,  Atanu R. Sinha

    IPC: G06K9/62 ,  G06F17/18 ,  G06N20/00 ,  G06F3/0481

    Abstract: In implementations of systems for predicting a terminal event, a computing device implements a termination system to receive input data defining a period of time and a maximum event threshold. This system uses a classification model to generate event scores for a plurality of entity devices. Each of the event scores indicates a probability of an event occurrence for a corresponding entity device within a period of time. The plurality of entity devices are segmented into a first segment and a second segment based on an event score threshold. Entity devices included in the first segment have event scores greater than the event score threshold and entity devices included in the second segment have event scores below the event score threshold. The termination system generates an indication of a probability that a number of event occurrences for the entity devices included in the second segment exceeds the maximum even threshold within the period of time.

    SYSTEMS AND METHODS FOR INDICATOR IDENTIFICATION
    19.
    发明公开
    SYSTEMS AND METHODS FOR INDICATOR IDENTIFICATION 审中-公开

    公开(公告)号：US20240232702A1

    公开(公告)日：2024-07-11

    申请号：US18152879

    申请日：2023-01-11

    Applicant: ADOBE INC.

    Inventor： Aurghya Maiti ,  Iftikhar Ahamath Burhanuddin ,  Atanu R. Sinha ,  Saurabh Mahapatra ,  Fan Du

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: One aspect of a method for data processing includes identifying target time series data for a target metric and candidate time series data for a plurality of indicators predictive of the target metric; training a machine learning model to predict the target time series data based on the candidate time series data; computing first through third predictivity values based on the machine learning model, wherein the first predictivity value indicates that a source indicator from the plurality of indicators is predictive of the target metric, the second predictivity value indicates that an intermediate indicator from the plurality of indicators is predictive of the target metric, and the third predictivity value indicates that the source indicator is predictive of the intermediate indicator; and displaying a portion of the candidate time series data corresponding to the intermediate indicator and the source indicator based on the first through third predictivity values.

Patent Agency Ranking