公开(公告)号：US11775582B2

公开(公告)日：2023-10-03

申请号：US18069561

申请日：2022-12-21

Applicant: Adobe Inc.

Inventor： Shenyu Xu ,  Eunyee Koh ,  Fan Du ,  Tak Yeon Lee ,  Sana Malik Lee ,  Ryan Rossi

IPC: G06F16/30 ,  G06F16/738 ,  G06F16/901 ,  G06F16/783 ,  G06F16/34 ,  G06F16/9032 ,  G06F16/44

CPC classification number: G06F16/739 ,  G06F16/345 ,  G06F16/44 ,  G06F16/7834 ,  G06F16/9024 ,  G06F16/90332

Abstract: This disclosure describes one or more embodiments of systems, non-transitory computer-readable media, and methods that intelligently and automatically analyze input data and generate visual data stories depicting graphical visualizations from data insights determined from the input data. For example, the disclosed systems automatically extract data insights utilizing an in-depth statistical analysis of dataset groups from data-attribute categories within the input data. Based on the data insights, the disclosed systems can automatically generate exportable visual data stories to visualize the data insights, provide textual or audio-based natural language summaries of the data insights, and animate such data insights in videos. In some embodiments, the disclosed systems generate a visual-data-story graph comprising nodes representing visual data stories and edges representing similarities between the visual data stories. Based on the visual-data-story graph, the disclosed systems can select a relevant visual data story to display on a graphical user interface.

公开(公告)号：US20220300836A1

公开(公告)日：2022-09-22

申请号：US17207959

申请日：2021-03-22

Applicant: Adobe Inc.

Inventor： Ryan Rossi ,  Xin Qian ,  Tak Yeon Lee ,  Sungchul Kim ,  Sana Lee ,  Fan Du ,  Eunyee Koh

IPC: G06N5/04 ,  G06N20/00

Abstract: A visualization recommendation system generates recommendation scores for multiple visualizations that combine data attributes of a dataset with visualization configurations. The visualization recommendation system maps meta-features of the dataset to a meta-feature space and configuration attributes of the visualization configurations to a configuration space. The visualization recommendation system generates meta-feature vectors that describe the mapped meta-features, and generates configuration attribute sets that describe the attributes of the visualization configurations. The visualization recommendation system applies multiple scoring models to the meta-feature vectors and configuration attribute sets, including a wide scoring model and a deep scoring model. In some cases, the visualization recommendation system trains the multiple scoring models using the meta-feature vectors and configuration attribute sets.

公开(公告)号：US20220147708A1

公开(公告)日：2022-05-12

申请号：US17094435

申请日：2020-11-10

Applicant: Adobe Inc.

Inventor： Eunyee Koh ,  Xin Qian ,  Tak Yeon Lee ,  Sana Malik Lee ,  Ryan Anthony Rossi ,  Fan Du ,  Duy-Trung Trong Dinh

IPC: G06F40/216

Abstract: A dataset captioning system is described that generates captions of text to describe insights identified from a dataset, automatically and without user intervention. To do so, given an input of a dataset the dataset captioning system determines which data insights are likely to support potential visualizations of the dataset, generates text based on these insights, orders the text, processes the ordered text for readability, and then outputs the text as a caption. These techniques also include adjustments made to the complexity of the text, globalization of the text, inclusion of links to outside sources of information, translation of the text, and so on as part of generating the caption.

公开(公告)号：US20220147540A1

公开(公告)日：2022-05-12

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: G06F16/26 ,  G06F11/30 ,  G06F11/34 ,  G06F3/0482

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.

公开(公告)号：US11341204B2

公开(公告)日：2022-05-24

申请号：US16419676

申请日：2019-05-22

Applicant: Adobe Inc.

Inventor： Tak Yeon Lee ,  Jonggi Hong ,  Eunyee Koh

IPC: G06F16/955 ,  G06N20/00 ,  G06F9/451 ,  G06F16/93

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for determining and resolving misalignments between digital messages containing links and corresponding external digital content. For example, in one or more embodiments, the disclosed systems extract a plurality of alignment classification features from a digital link in a digital message and corresponding external digital content. Based on the alignment classification features and using a machine learning classification model, the disclosed system can generate alignment probability scores for a plurality of misalignment classes. The disclosed system can report identified misalignments of corresponding misalignment classes in a misalignment identification user interface. Furthermore, the disclosed system can receive publisher input via the misalignment identification user interface to further personalize the machine learning classification model.

公开(公告)号：US20210232908A1

公开(公告)日：2021-07-29

申请号：US16751755

申请日：2020-01-24

Applicant: Adobe Inc.

Inventor： Yikun Xian ,  Tak Yeon Lee ,  Sungchul Kim ,  Ryan Rossi ,  Handong Zhao

IPC: G06N3/08

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for dynamically determining schema labels for columns regardless of information availability within the columns. For example, the disclosed systems can identify a column that contains an arbitrary amount of information (e.g., a header-only column, a cell-only column, or a whole column). Additionally, the disclosed systems can generate a vector embedding for an arbitrary input column by selectively using a header neural network and/or a cell neural network based on whether the column includes a header label and/or whether the column includes a populated column cell. Furthermore, the disclosed systems can compare the column vector embedding to schema vector embeddings of candidate schema labels in a d-dimensional space to determine a schema label for the column.

公开(公告)号：US20190272559A1

公开(公告)日：2019-09-05

申请号：US15910926

申请日：2018-03-02

Applicant: Adobe Inc.

Inventor： Tak Yeon Lee ,  Eunyee Koh

IPC: G06Q30/02 ,  G06F17/27

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for determining and resolving semantic misalignments between digital messages containing links and corresponding external digital content. For example, in one or more embodiments, the disclosed systems compare semantic message features from the digital message with semantic external digital content features from the external digital content. More specifically, in at least one embodiment, the disclosed systems compare semantic message feature vectors and semantic external digital content feature vectors to determine a relevance score for the digital message and identify semantic misalignments. Additionally, in one or more embodiments, the disclosed systems provide for display a user interface that presents a plurality of digital messages, the linked external digital content, and identified semantic misalignments.

公开(公告)号：US11995048B2

公开(公告)日：2024-05-28

申请号：US17036453

申请日：2020-09-29

Applicant: ADOBE INC.

Inventor： Handong Zhao ,  Yikun Xian ,  Sungchul Kim ,  Tak Yeon Lee ,  Nikhil Belsare ,  Shashi Kant Rai ,  Vasanthi Holtcamp ,  Thomas Jacobs ,  Duy-Trung T Dinh ,  Caroline Jiwon Kim

IPC: G06F16/00 ,  G06F16/21 ,  G06F18/2115 ,  G06F18/214 ,  G06F18/2431 ,  G06N3/08 ,  G06V30/262

CPC classification number: G06F16/213 ,  G06F18/2115 ,  G06F18/2148 ,  G06F18/2431 ,  G06N3/08 ,  G06V30/274

Abstract: Systems and methods for lifelong schema matching are described. The systems and methods include receiving data comprising a plurality of information categories, classifying each information category according to a schema comprising a plurality of classes, wherein the classification is performed by a neural network classifier trained based on a lifelong learning technique using a plurality of exemplar training sets, wherein each of the exemplar training sets includes a plurality of examples corresponding to one of the classes, and wherein the examples are selected based on a metric indicating how well each of the examples represents the corresponding class, and adding the data to a database based on the classification, wherein the database is organized according to the schema.

公开(公告)号：US11782576B2

公开(公告)日：2023-10-10

申请号：US17161770

申请日：2021-01-29

Applicant: Adobe Inc.

Inventor： Camille Harris ,  Zening Qu ,  Sana Lee ,  Ryan Rossi ,  Fan Du ,  Eunyee Koh ,  Tak Yeon Lee ,  Sungchul Kim ,  Handong Zhao ,  Sumit Shekhar

IPC: G06F3/0482 ,  G06F17/15 ,  G06F3/04845

CPC classification number: G06F3/0482 ,  G06F3/04845 ,  G06F17/15

Abstract: In some embodiments, a data visualization system detects insights from a dataset and computes insight scores for respective insights. The data visualization system further computes insight type scores, from the insight scores, for insight types in the detected insights. The data visualization system determines a selected insight type for the dataset having a higher insight type score than unselected insight types and determines, for the selected insight type, a set of selected insights that have higher insight scores than unselected insights. The data visualization system determines insight visualizations for the set of selected insights and generates, for inclusion in a user interface of the data visualization system, selectable interface elements configured for invoking an editing tool for updating the determined insight visualizations from the dataset. The selectable interface elements are arranged in the user interface according to the insight scores of the set of selected insights.

公开(公告)号：US11645523B2

公开(公告)日：2023-05-09

申请号：US16796681

申请日：2020-02-20

Applicant: Adobe Inc.

Inventor： Yikun Xian ,  Tak Yeon Lee ,  Sungchul Kim ,  Ryan Rossi ,  Handong Zhao

IPC: G06F16/22 ,  G06F16/2457 ,  G06F16/248 ,  G06F16/901 ,  G06N3/08 ,  G06N5/02

CPC classification number: G06N3/08 ,  G06F16/221 ,  G06F16/248 ,  G06F16/24578 ,  G06F16/9024 ,  G06N5/02

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for generating generate explanatory paths for column annotations determined using a knowledge graph and a deep representation learning model. For instance, the disclosed systems can utilize a knowledge graph to generate an explanatory path for a column label determination from a deep representation learning model. For example, the disclosed systems can identify a column and determine a label for the column using a knowledge graph (e.g., a representation of a knowledge graph) that includes encodings of columns, column features, relational edges, and candidate labels. Then, the disclosed systems can determine a set of candidate paths between the column and the determined label for the column within the knowledge graph. Moreover, the disclosed systems can generate an explanatory path by ranking and selecting paths from the set of candidate paths using a greedy ranking and/or diversified ranking approach.