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公开(公告)号：US12072839B2
公开(公告)日：2024-08-27
申请号：US17544705
申请日：2021-12-07
Applicant: GOOGLE LLC
Inventor： Weize Kong , Mingyang Zhang , Michael Bendersky , Marc Alexander Najork , Mike Colagrosso , Brandon Vargo , Remy Burger
CPC classification number: G06F16/122 , G06F16/18
Abstract: Techniques are described herein for enabling more computationally efficient organization of files within a cloud storage system. A method includes: receiving information identifying a document and a set of folders; for each folder in the set of folders, using a trained model to predict a similarity measure between the folder and the document; for each folder in the set of folders, determining a score for the folder based on the predicted similarity measure for the folder; selecting a candidate folder from the set of folders using the scores of the folders within the set of folders; and providing, on a user interface, a selectable option to associate the document with the candidate folder.
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Patent Agency Ranking
公开(公告)号：US20250103640A1
公开(公告)日：2025-03-27
申请号：US18472190
申请日：2023-09-21
Applicant: Google LLC
Inventor： Zachary Dicklin , Michael Colagrosso , Remy Burger , Michael Bendersky , Brandon Vargo
Abstract: Systems and methods include pre-processing documents in cloud storage using query embeddings, providing personalized prompts to users based on documents in cloud storage, real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers including citation to source documents in cloud storage. The system and methods generate generative machine learning model (MLM) prompts based on document portions of documents in a cloud-based content management platform. The systems and methods use the generative MLM to generate responses to prompts, and the responses include citations to the document portions used to generate the responses in order for users to verify the responses.
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3.发明申请公开(公告)号：US20250103867A1
公开(公告)日：2025-03-27
申请号：US18472178
申请日：2023-09-21
Applicant: Google LLC
Inventor： Zachary Dicklin , Michael Colagrosso , Remy Burger , Michael Bendersky , Brandon Vargo
IPC: G06N3/0475
Abstract: Systems and methods include pre-processing documents in cloud storage using query embeddings, providing personalized prompts to users based on documents in cloud storage, real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers including citation to source documents in cloud storage. The system and methods generate generative machine learning model (MLM) prompts based on document portions of documents in a cloud-based content management platform. The systems and methods use the generative MLM to generate responses to prompts, and the responses include citations to the document portions used to generate the responses in order for users to verify the responses.
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公开(公告)号：US20250103827A1
公开(公告)日：2025-03-27
申请号：US18472167
申请日：2023-09-21
Applicant: Google LLC
Inventor： Zachary Dicklin , Michael Colagrosso , Remy Burger , Michael Bendersky , Brandon Vargo
IPC: G06F40/40 , G06F16/34 , G06F16/383
Abstract: Systems and methods include pre-processing documents in cloud storage using query embeddings, providing personalized prompts to users based on documents in cloud storage, real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers including citation to source documents in cloud storage. The system and methods generate generative machine learning model (MLM) prompts based on document portions of documents in a cloud-based content management platform. The systems and methods use the generative MLM to generate responses to prompts, and the responses include citations to the document portions used to generate the responses in order for users to verify the responses.
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公开(公告)号：US20250103826A1
公开(公告)日：2025-03-27
申请号：US18472156
申请日：2023-09-21
Applicant: Google LLC
Inventor： Zachary Dicklin , Michael Colagrosso , Remy Burger , Michael Bendersky , Brandon Vargo
IPC: G06F40/40 , G06F16/9032 , G06F16/906 , G06F16/93 , G06N20/00
Abstract: Systems and methods include pre-processing documents in cloud storage using query embeddings, providing personalized prompts to users based on documents in cloud storage, real-time anticipation of user interest in information contained in documents in cloud storage, and providing generative answers including citation to source documents in cloud storage. The system and methods generate generative machine learning model (MLM) prompts based on document portions of documents in a cloud-based content management platform. The systems and methods use the generative MLM to generate responses to prompts, and the responses include citations to the document portions used to generate the responses in order for users to verify the responses.
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公开(公告)号：US20230177004A1
公开(公告)日：2023-06-08
申请号：US17544705
申请日：2021-12-07
Applicant: GOOGLE LLC
Inventor： Weize Kong , Mingyang Zhang , Michael Bendersky , Marc Alexander Najork , Mike Colagrosso , Brandon Vargo , Remy Burger
CPC classification number: G06F16/122 , G06F16/18
Abstract: Techniques are described herein for enabling more computationally efficient organization of files within a cloud storage system. A method includes: receiving information identifying a document and a set of folders; for each folder in the set of folders, using a trained model to predict a similarity measure between the folder and the document; for each folder in the set of folders, determining a score for the folder based on the predicted similarity measure for the folder; selecting a candidate folder from the set of folders using the scores of the folders within the set of folders; and providing, on a user interface, a selectable option to associate the document with the candidate folder.
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