公开(公告)号：US20240311581A1

公开(公告)日：2024-09-19

申请号：US18185547

申请日：2023-03-17

Applicant: ADOBE INC.

Inventor： Arpit Narechania ,  Fan Du ,  Atanu Sinha ,  Nedim Lipka ,  Alexa F. Siu ,  Jane Elizabeth Hoffswell ,  Eunyee Koh ,  Vasanthi Holtcamp

IPC: G06F40/40 ,  G06F40/279 ,  G06F40/30 ,  G06V30/19 ,  G06V30/412

CPC classification number: G06F40/40 ,  G06F40/279 ,  G06F40/30 ,  G06V30/19147 ,  G06V30/412

Abstract: Aspects of the method, apparatus, non-transitory computer readable medium, and system include obtaining a document and an information element. The aspects further include identifying, from the document, an anchor element that has an anchor type and a relationship type, wherein the anchor type describes a structure of a set of anchor elements, and the relationship type describes a relationship between the anchor element and the information element. The aspects further include extracting information corresponding to the information element based on the anchor element, the anchor type, and the relationship type, and displaying the extracted information to a user.

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：US20220148013A1

公开(公告)日：2022-05-12

申请号：US17091569

申请日：2020-11-06

Applicant: ADOBE INC.

Inventor： RITWIK SINHA ,  Fan Du ,  Sunav Choudhary ,  Sanket Mehta ,  Harvineet Singh ,  Said Kobeissi ,  William Brandon George ,  Chris Challis ,  Prithvi Bhutani ,  John Bates ,  Ivan Andrus

IPC: G06Q30/02 ,  G06F16/904 ,  G06F17/18

Abstract: Determination of high value customer journey sequences is performed by determining customer interactions that are most frequent as length N=1 sub-sequences, recursively determining most frequent length N+1 sub-sequences that start with the length N sub-sequences, determining a first count indicating how often one of the sub-sequences appears in the sequences, determining a second count indicating how often the one sub-sequence resulted in the goal, and using the counts to determine the most or least effective sub-sequences for achieving the goal.

公开(公告)号：US12216677B2

公开(公告)日：2025-02-04

申请号：US18328980

申请日：2023-06-05

Applicant: ADOBE INC.

Inventor： Chen Chen ,  Jane Elizabeth Hoffswell ,  Shunan Guo ,  Fan Du ,  Nathan Carl Ross ,  Ryan A. Rossi ,  Yeuk Yin Chan ,  Eunyee Koh

IPC: G06F16/26 ,  G06F3/0482 ,  G06F16/248 ,  G06T11/20

Abstract: Systems and methods for data analysis are described. Embodiments of the present disclosure data analysis include displaying, via a data analysis interface, a data visualization in a first region of the data analysis interface; and displaying, via the data analysis interface, an analysis thread visualization in a second region of the data analysis interface. The analysis thread visualization depicts an analysis thread graph including a first node corresponding to the data visualization and an edge corresponding to an analysis path between the first node and a second node.

公开(公告)号：US20240403313A1

公开(公告)日：2024-12-05

申请号：US18328980

申请日：2023-06-05

Applicant: ADOBE INC.

Inventor： Chen Chen ,  Jane Elizabeth Hoffswell ,  Shunan Guo ,  Fan Du ,  Nathan Carl Ross ,  Ryan A. Rossi ,  Yeuk Yin Chan ,  Eunyee Koh

IPC: G06F16/26 ,  G06F16/248 ,  G06T11/20

Abstract: Systems and methods for data analysis are described. Embodiments of the present disclosure data analysis include displaying, via a data analysis interface, a data visualization in a first region of the data analysis interface; and displaying, via the data analysis interface, an analysis thread visualization in a second region of the data analysis interface. The analysis thread visualization depicts an analysis thread graph including a first node corresponding to the data visualization and an edge corresponding to an analysis path between the first node and a second node.

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：US11720590B2

公开(公告)日：2023-08-08

申请号：US17091941

申请日：2020-11-06

Applicant: ADOBE INC.

Inventor： Ryan Rossi ,  Vasanthi Holtcamp ,  Tak Yeon Lee ,  Sungchul Kim ,  Sana Lee ,  Nathan Ross ,  John Anderson ,  Fan Du ,  Eunyee Koh ,  Xin Qian

IPC: G06F16/9535 ,  G06F16/26 ,  G06F3/0482 ,  G06F11/34 ,  G06F11/30 ,  G06F16/9038

CPC classification number: G06F16/26 ,  G06F3/0482 ,  G06F11/302 ,  G06F11/3438 ,  G06F16/9038

Abstract: Systems and methods for personalized visualization recommendation are described. Embodiments of the described systems and methods are configured to identify a first matrix representing user interactions with a plurality of data attributes corresponding to a plurality of datasets, a second matrix representing user interactions with a plurality of visualizations, and a third matrix representing a plurality of meta-features for each of the data attributes; compute low-dimensional embeddings representing user characteristics, the data attributes, visualization configurations, and the meta-features using joint factorization of the first matrix, the second matrix and the third matrix; generate a model for predicting visualization preference weights based on the low-dimensional embeddings; predict the visualization preference weights for a user corresponding to a plurality of candidate visualizations of dataset using the model; and generate a personalized visualization of the dataset for the user based on the predicted visualization preference weights.