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：US20230418881A1

公开(公告)日：2023-12-28

申请号：US17809371

申请日：2022-06-28

Applicant: ADOBE INC.

Inventor： Shunan Guo ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Caroline Jiwon Kim ,  Cole Edward Connelly ,  Andrew Douglas Thomson

IPC: G06F16/93 ,  G06F40/103 ,  G06F40/14 ,  G06F40/166

CPC classification number: G06F16/93 ,  G06F40/103 ,  G06F40/14 ,  G06F40/166

Abstract: Systems and methods for document generation are provided. One aspect of the systems and methods includes identifying, by a style extractor, a document fragment comprising a first style element of a first style category; computing, by a style generator, a reward function based on a correlation value between the first style element and a second style element of a second style category different from the first style category, wherein the correlation value is based on correlations between style elements in a plurality of historical document fragments; selecting, by the style generator, the second style element based on the reward function; and generating, by a document generator, a modified document fragment that includes the first style element of the first style category and the second style element of the second style category.

公开(公告)号：US20220253463A1

公开(公告)日：2022-08-11

申请号：US17660328

申请日：2022-04-22

Applicant: Adobe Inc.

Inventor： Fan Du ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Ryan Rossi ,  Margarita Savova ,  Charles Menguy ,  Anup Rao

IPC: G06F16/28 ,  G06F16/22 ,  G06F16/14 ,  G06F16/84 ,  G06F16/2458 ,  G06F16/909

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.

公开(公告)号：US12164517B2

公开(公告)日：2024-12-10

申请号：US18092779

申请日：2023-01-03

Applicant: Adobe Inc.

Inventor： Vibhor Porwal ,  Yeuk-Yin Chan ,  Vidit Bhatia ,  Subrata Mitra ,  Shaddy Garg ,  Sergey N Kazarin ,  Sameeksha Arora ,  Himanshu Panday ,  Gautam Pratap Kowshik ,  Fan Du ,  Anup Bandigadi Rao ,  Anil Malkani

IPC: G06F16/245 ,  G06F16/2453 ,  G06F16/2458

Abstract: To retrieve information derived from a plurality of separately stored datasets, join structures are identified within the plurality of separately stored datasets. Join structures can include datasets joined by a central dataset, datasets joined by a single key, and datasets joined across a plurality of keys. Each of the join structures corresponds to a query processing schema that defines a sampling technique. When a join query is received as a SQL query, the join query identifies a portion of the plurality of separately stored datasets, from which a join structure is selected and a corresponding query processing schema is identified. The join query is reconstructed to form a reconstructed join query that comprises query processing schema instructions to derive the requested information using the sampling technique defined by the identified query processing schema.

公开(公告)号：US11328002B2

公开(公告)日：2022-05-10

申请号：US16852110

申请日：2020-04-17

Applicant: Adobe Inc.

Inventor： Fan Du ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Ryan Rossi ,  Margarita Savova ,  Charles Menguy ,  Anup Rao

IPC: G06F16/00 ,  G06F16/28 ,  G06F16/22 ,  G06F16/14 ,  G06F16/84 ,  G06F16/2458 ,  G06F16/909

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.

公开(公告)号：US11630854B2

公开(公告)日：2023-04-18

申请号：US17660328

申请日：2022-04-22

Applicant: Adobe Inc.

Inventor： Fan Du ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Ryan Rossi ,  Margarita Savova ,  Charles Menguy ,  Anup Rao

IPC: G06F16/00 ,  G06F16/28 ,  G06F16/22 ,  G06F16/14 ,  G06F16/84 ,  G06F16/2458 ,  G06F16/909

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.

公开(公告)号：US20210326361A1

公开(公告)日：2021-10-21

申请号：US16852110

申请日：2020-04-17

Applicant: Adobe Inc.

Inventor： Fan Du ,  Yeuk-Yin Chan ,  Eunyee Koh ,  Ryan Rossi ,  Margarita Savova ,  Charles Menguy ,  Anup Rao

IPC: G06F16/28 ,  G06F16/22

Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing hash partitions to determine local densities and distances among users (or among other represented data points) for clustering sparse data into segments. For instance, the disclosed systems can generate hash signatures for users in a sparse dataset and can map users to hash partitions based on the hash signatures. The disclosed systems can further determine local densities and separation distances for particular users (or other represented data points) within the hash partitions. Upon determining local densities and separation distances for datapoints from the dataset, the disclosed systems can select a segment (or cluster of data points) grouped according to a hierarchy of a clustering algorithm, such as a density-peaks-clustering algorithm.