公开(公告)号：US11455466B2

公开(公告)日：2022-09-27

申请号：US16490440

申请日：2019-05-01

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Xingxing Zhang ,  Ji Li ,  Furu Wei ,  Ming Zhou ,  Amit Srivastava

IPC: G06F40/274 ,  G06N20/00 ,  G06N3/08

Abstract: A method and system for providing an application-specific embedding for an entire text-to-content suggestions service is disclosed. The method includes accessing a dataset containing unlabeled training data collected from an application, the unlabeled training data being collected under user privacy constraints, applying an unsupervised ML model to the dataset to generate a pretrained embedding; and utilizing the pretrained embedding to train the text-to-content suggestion ML model utilized by the application.

公开(公告)号：US12124812B2

公开(公告)日：2024-10-22

申请号：US17510850

申请日：2021-10-26

Applicant: Microsoft Technology Licensing, LLC

Inventor： Ji Li ,  Amit Srivastava ,  Xingxing Zhang ,  Furu Wei

IPC: G06F40/56 ,  G06F40/284 ,  G06F40/47

CPC classification number: G06F40/56 ,  G06F40/284 ,  G06F40/47

Abstract: A data processing system implements obtaining first textual content in a first language from a first client device; determining that the first language is supported by a first machine learning model; obtaining a guard list of prohibited terms associated with the first language; determining that the textual content does not include one or more prohibited terms associated based on the guard list; providing the first textual content as an input to the first machine learning model responsive to the textual content not including the one or more prohibited terms; analyzing the first textual content with the first machine learning model to obtain a first content recommendation; obtaining a first content recommendation policy that identifies content associated with the first language that may not be provided as a content recommendation; determining that the first content recommendation is not prohibited; and providing the first content recommendation to the first client device.

公开(公告)号：US12050636B2

公开(公告)日：2024-07-30

申请号：US17056728

申请日：2019-06-17

Applicant: Microsoft Technology Licensing, LLC

Inventor： Xingxing Zhang ,  Shaohan Huang ,  Lei Cui ,  Tao Ge ,  Furu Wei ,  Ming Zhou

IPC: G06F16/34 ,  G06F18/213 ,  G06F18/214 ,  G06F40/30 ,  G06V30/262 ,  G06V30/413

CPC classification number: G06F16/345 ,  G06F18/213 ,  G06F18/214 ,  G06F40/30 ,  G06V30/274 ,  G06V30/413

Abstract: According to implementations of the subject matter described herein, there is provided a solution for generating a summary of a document. In this solution, feature information of pages comprised in a document is extracted, which characterizes at least one type of content contained in each page. Respective importance of the pages is determined at least based on the extracted feature information. A summary of the document is generated for the document by selecting a predetermined number of pages less than the number of the pages based on the respective importance. Through the solution, instead of providing all the pages, pages containing important content may be determined automatically to serve as the summary of the document. This summary allows the user to learn quickly main content of the document, shorten the time consumed in browsing all documents and/or facilitate location of a document of interest as soon as possible.

公开(公告)号：US11727270B2

公开(公告)日：2023-08-15

申请号：US16799091

申请日：2020-02-24

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Ji Li ,  Amit Srivastava ,  Xingxing Zhang ,  Furu Wei ,  Ming Zhou

IPC: G06F40/40 ,  G06N3/08 ,  G06F40/205 ,  G06F18/214 ,  G10L15/16 ,  G10L15/18 ,  G06N3/088 ,  G06F40/30

CPC classification number: G06N3/08 ,  G06F18/2148 ,  G06F40/205 ,  G06F40/40 ,  G06F40/30 ,  G06N3/088 ,  G10L15/16 ,  G10L15/18

Abstract: A method and system for training a text-to-content recommendation ML model includes training a first ML model using a first training data set, utilizing the trained first ML model to infer information about the data contained in the first training data set, collecting the inferred information to generate a second training data set, and utilizing the first training data set and the second training data set to train a second ML model. The second ML model may be a text-to-content recommendation ML model.

公开(公告)号：US11429787B2

公开(公告)日：2022-08-30

申请号：US16490456

申请日：2019-05-01

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Ji Li ,  Xingxing Zhang ,  Furu Wei ,  Ming Zhou ,  Amit Srivastava

IPC: G06F40/274 ,  G06N20/20 ,  G06F40/40

Abstract: Method and system for training a text-to-content suggestion ML model include accessing a dataset containing unlabeled training data collected from an application, the unlabeled training data being collected under user privacy constraints, applying an ML model to the dataset to generate a pretrained embedding, and applying a supervised ML model to a labeled dataset to train the text-to-content suggestion ML model utilized by the application by utilizing the pretrained embedding generated by the supervised ML model.