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    Self-supervised system generating embeddings representing sequenced activity
    21.
    发明授权
    Self-supervised system generating embeddings representing sequenced activity 有权

    公开(公告)号：US12062059B2

    公开(公告)日：2024-08-13

    申请号：US16930279

    申请日：2020-07-15

    申请人： Microsoft Technology Licensing, LLC

    发明人： Mayank Shrivastava ,  Sagar Goyal ,  Sahil Bhatnagar ,  Pin-Jung Chen ,  Pushpraj Shukla ,  Arko P. Mukherjee

    IPC分类号： G06Q30/0202 ,  G06N3/04 ,  G06N3/084 ,  G06N20/00

    CPC分类号： G06Q30/0202 ,  G06N3/04 ,  G06N3/084 ,  G06N20/00

    摘要： The disclosure herein describes a system for generating embeddings representing sequential human activity by self-supervised, deep learning models capable of being utilized by a variety of machine learning prediction models to create predictions and recommendations. An encoder-decoder is provided to create user-specific journeys, including sequenced events, based on human activity data from a plurality of tables, a customer data platform, or other sources. Events are represented by sequential feature vectors. A user-specific embedding representing user activities in relationship to activities of one or more other users is created for each user in a plurality of users. The embeddings are updated in real-time as new activity data is received. The embeddings can be fine-tuned using labeled data to customize the embeddings for a specific predictive model. The embeddings are utilized by predictive models to create product recommendations and predictions, such as customer churn, next steps in a customer journey, etc.

    Rapid region wide production forecasting
    23.
    发明授权
    Rapid region wide production forecasting 有权

    公开(公告)号：US12056726B2

    公开(公告)日：2024-08-06

    申请号：US17310185

    申请日：2020-01-24

    申请人： Schlumberger Technology Corporation

    发明人： Erik Burton ,  Andrey Konchenko ,  Emilien Dupont

    IPC分类号： G06Q30/0202 ,  G06N20/00 ,  G06Q10/04 ,  G06Q50/02

    CPC分类号： G06Q30/0202 ,  G06N20/00 ,  G06Q10/04 ,  G06Q50/02 ,  E21B2200/20

    摘要： A method for rapid region wide production forecasting includes identifying base data of a well in a plurality of wells of a region; selecting, using the base data and from a set of a models comprising a rich machine learning model, a location based machine learning model, and a decline curve model, a well model; and generating, based on the selecting, a forecasted production of the well using the base data and the well model. The method further includes aggregating a plurality of forecasted productions of the plurality of wells, the plurality of forecasted productions including the forecasted production, to generate a region forecast using the rich machine learning model, the location based machine learning model, and the decline curve model; and presenting the region forecast.

    METHOD AND SYSTEM FOR WEB-BASED MANAGEMENT OF CONSUMER PACKAGED GOODS
    27.
    发明公开
    METHOD AND SYSTEM FOR WEB-BASED MANAGEMENT OF CONSUMER PACKAGED GOODS 审中-公开

    公开(公告)号：US20240249297A1

    公开(公告)日：2024-07-25

    申请号：US18420650

    申请日：2024-01-23

    申请人： OnePage Software, LLC

    发明人： Miles Dickinson ,  Ryan Moore

    IPC分类号： G06Q30/0202 ,  G06Q10/08 ,  G06Q30/0207

    CPC分类号： G06Q30/0202 ,  G06Q10/08 ,  G06Q30/0207

    摘要： Methods and systems for web-based management of consumer packaged goods (CPG). In an exemplary method, the management can be implemented at one or more nodes of supplying a product. A computing system can receive at least one input parameter associated with a first selected node of the nodes, and a request to generate a forecast for at least one output parameter based upon the input parameter. The computing system can generate the forecast based upon a database storing data of the nodes and upon implementing a model with the data and the input parameter. The method offers an integrated solution allowing all departments managing the CPG to leverage data to inform their specific use-cases. The bottom-up architecture ties customer DCs to retailers, and ties customer DCs to manufacturer DCs, allowing an integrated approach aligning the needs across all departments to a single system, resulting in a holistically better forecast.