公开(公告)号：US11836172B2

公开(公告)日：2023-12-05

申请号：US17354954

申请日：2021-06-22

Applicant: ADOBE INC.

Inventor： Fan Du ,  Zening Qu ,  Vasanthi Swaminathan Holtcamp ,  Tak Yeon Lee ,  Sungchul Kim ,  Saurabh Mahapatra ,  Sana Malik Lee ,  Ryan A. Rossi ,  Nikhil Belsare ,  Eunyee Koh ,  Andrew Thomson ,  Sumit Shekhar

IPC: G06F16/33 ,  G06N5/046 ,  G06F16/338

CPC classification number: G06F16/3344 ,  G06F16/338 ,  G06F16/3346 ,  G06N5/046

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.

公开(公告)号：US20230306194A1

公开(公告)日：2023-09-28

申请号：US17656254

申请日：2022-03-24

Applicant: ADOBE INC.

Inventor： Fan Du ,  Cameron Elise Womack ,  Dylan Robert Kario ,  Molly Josette Bloom ,  Elizabeth Waters ,  Matthew Samuel Deutsch ,  Ryan Wilkes ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Andrew Douglas Thomson ,  Cole Edward Connelly ,  Saurabh Mahapatra ,  Vasanthi Holtcamp

IPC: G06F40/186 ,  G06F40/143 ,  G06F40/177 ,  G06K9/62 ,  G06N5/02 ,  G06N5/00

CPC classification number: G06F40/186 ,  G06F40/143 ,  G06F40/177 ,  G06K9/6218 ,  G06N5/025 ,  G06N5/003

Abstract: Systems and methods for data processing are described. Example embodiments include identifying chart data corresponding to a visual element of a user interface; selecting an insight type based on a chart category of the chart data; generating insight data for the insight type based on the chart data using a statistical measure corresponding to the insight type; generating an insight caption for the insight type by combining the insight data with a sentence template corresponding to the insight type; and communicating the insight caption to a user of the user interface.

公开(公告)号：US12206925B2

公开(公告)日：2025-01-21

申请号：US17813622

申请日：2022-07-20

Applicant: ADOBE INC.

Inventor： Atanu R. Sinha ,  Aurghya Maiti ,  Atishay Ganesh ,  Saili Myana ,  Harshita Chopra ,  Sarthak Kapoor ,  Saurabh Mahapatra

IPC: H04N21/25 ,  H04N21/2668

Abstract: Systems and methods for content customization are provided. One aspect of the systems and methods includes receiving dynamic characteristics for a plurality of users, wherein the dynamic characteristics include interactions between the plurality of users and a digital content channel; clustering the plurality of users in a plurality of segments based on the dynamic characteristics using a machine learning model; assigning a user to a segment of the plurality of segments based on static characteristics of the user; and providing customized digital content for the user based on the segment.

公开(公告)号：US12045272B2

公开(公告)日：2024-07-23

申请号：US17370899

申请日：2021-07-08

Applicant: ADOBE INC.

Inventor： Saurabh Mahapatra ,  Niyati Chhaya ,  Snehal Raj ,  Sharmila Reddy Nangi ,  Sapthotharan Nair ,  Sagnik Mukherjee ,  Jay Mundra ,  Fan Du ,  Atharv Tyagi ,  Aparna Garimella

IPC: G06F16/34 ,  G06F16/332 ,  G06F40/30 ,  G06N3/04 ,  G06N3/044 ,  G06N3/08

CPC classification number: G06F16/345 ,  G06F16/3329 ,  G06F40/30 ,  G06N3/04 ,  G06N3/044 ,  G06N3/08

Abstract: A text summarization system auto-generates text summarization models using a combination of neural architecture search and knowledge distillation. Given an input dataset for generating/training a text summarization model, neural architecture search is used to sample a search space to select a network architecture for the text summarization model. Knowledge distillation includes fine-tuning a language model for a given text summarization task using the input dataset, and using the fine-tuned language model as a teacher model to inform the selection of the network architecture and the training of the text summarization model. Once a text summarization model has been generated, the text summarization model can be used to generate summaries for given text.

公开(公告)号：US20220405314A1

公开(公告)日：2022-12-22

申请号：US17354954

申请日：2021-06-22

Applicant: ADOBE INC.

Inventor： Fan Du ,  Zening Qu ,  Vasanthi Swaminathan Holtcamp ,  Tak Yeon Lee ,  Sungchul Kim ,  Saurabh Mahapatra ,  Sana Malik Lee ,  Ryan A. Rossi ,  Nikhil Belsare ,  Eunyee Koh ,  Andrew Thomson ,  Sumit Shekhar

IPC: G06F16/33 ,  G06F16/338 ,  G06N5/04

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.

公开(公告)号：US20220383224A1

公开(公告)日：2022-12-01

申请号：US17329934

申请日：2021-05-25

Applicant: ADOBE INC.

Inventor： Atanu Sinha ,  Manoj Kilaru ,  Iftikhar Ahamath Burhanuddin ,  Aneesh Shetty ,  Titas Chakraborty ,  Rachit Bansal ,  Tirupati Saketh Chandra ,  Fan Du ,  Aurghya Maiti ,  Saurabh Mahapatra

IPC: G06Q10/06 ,  G06K9/62

Abstract: Systems and methods for data analytics are described. One or more embodiments of the present disclosure receive target time series data and candidate time series data, where the candidate time series data includes data corresponding to each of a plurality of candidate metrics, train a prediction network to predict the target time series data based on the candidate time series data by setting temporal attention weights corresponding to a plurality of rolling time windows and by setting candidate attention weights corresponding to the plurality of candidate metrics, identify a leading indicator metric for the target time series data from the plurality of candidate metrics based on the temporal attention weights and the candidate attention weights, and signal the leading indicator metric for the target time series data.

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.

公开(公告)号：US20230289696A1

公开(公告)日：2023-09-14

申请号：US17693778

申请日：2022-03-14

Applicant: ADOBE INC.

Inventor： Arpit Ajay Narechania ,  Fan Du ,  Atanu R. Sinha ,  Ryan A. Rossi ,  Jane Elizabeth Hoffswell ,  Shunan Guo ,  Eunyee Koh ,  John Anderson ,  Sonali Surange ,  Saurabh Mahapatra ,  Vasanthi Holtcamp

IPC: G06Q10/06

CPC classification number: G06Q10/06393 ,  G06F3/0482

Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality”—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle. For example, an interactive tree view may visually represent a nested attribute schema and attribute quality or consumption metrics to facilitate discovery of bad data before ingesting into a data lake.

公开(公告)号：US20230020886A1

公开(公告)日：2023-01-19

申请号：US17370899

申请日：2021-07-08

Applicant: ADOBE INC.

Inventor： Saurabh Mahapatra ,  Niyati Chhaya ,  Snehal Raj ,  Sharmila Reddy Nangi ,  Sapthotharan Nair ,  Sagnik Mukherjee ,  Jay Mundra ,  Fan Du ,  Atharv Tyagi ,  Aparna Garimella

IPC: G06F16/34 ,  G06F16/332 ,  G06N3/04 ,  G06N3/08

Abstract: A text summarization system auto-generates text summarization models using a combination of neural architecture search and knowledge distillation. Given an input dataset for generating/training a text summarization model, neural architecture search is used to sample a search space to select a network architecture for the text summarization model. Knowledge distillation includes fine-tuning a language model for a given text summarization task using the input dataset, and using the fine-tuned language model as a teacher model to inform the selection of the network architecture and the training of the text summarization model. Once a text summarization model has been generated, the text summarization model can be used to generate summaries for given text.

公开(公告)号：US20250061488A1

公开(公告)日：2025-02-20

申请号：US18451590

申请日：2023-08-17

Applicant: ADOBE INC.

Inventor： Atanu R. Sinha ,  Ryan A. Rossi ,  Sunav Choudhary ,  Harshita Chopra ,  Paavan Indela ,  Veda Pranav Parwatala ,  Srinjayee Paul ,  Saurabh Mahapatra ,  Aurghya Maiti

IPC: G06Q30/0251 ,  G06N20/00 ,  G06Q30/0204

Abstract: Systems and methods for delivery aware audience segmentation and subsequent delivery of content are described. Embodiments are configured to obtain activity data for a user, assign the user to a user segment based on the activity data using a machine learning model, generate a reach prediction for the user segment, select a media channel for communicating with the user based on the user segment and the reach prediction, and provide targeted content to the user via the selected media channel. According to some aspects, the machine learning model is trained based on content reach data.