公开(公告)号：US11113293B2

公开(公告)日：2021-09-07

申请号：US16252169

申请日：2019-01-18

Applicant: ADOBE INC.

Inventor： Di Jin ,  Ryan A. Rossi ,  Eunyee Koh ,  Sungchul Kim ,  Anup Rao

IPC: G06F16/24 ,  G06F16/2458 ,  G06F16/901 ,  G06F16/26 ,  G06F16/215 ,  G06F16/28

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for latent summarization of a graph. Structural features can be captured from feature vectors associated with each node of the graph by applying base functions on the feature vectors and iteratively applying relational operators to successive feature matrices to derive deeper inductive relational functions that capture higher-order structural information in different subgraphs of increasing size (node separations). Heterogeneity can be summarized by performing capturing features in appropriate subgraphs (e.g., node-centric neighborhoods associated with each node type, edge direction, and/or edge type). Binning and/or dimensionality reduction can be applied to the resulting feature matrices. The resulting set of relational functions and multi-level feature matrices can form a latent summary that can be used to perform a variety of graph-based tasks, including node classification, node clustering, link prediction, entity resolution, anomaly and event detection, and inductive learning tasks.

公开(公告)号：US10909571B2

公开(公告)日：2021-02-02

申请号：US14823121

申请日：2015-08-11

Applicant: Adobe Inc.

Inventor： Eunyee Koh ,  Rhema P. Linder

IPC: G06Q30/02

Abstract: Techniques are described in which a service operates to identify consumers corresponding to visitor interactions with resources available from a service provider. Features are selected to use for matching of clickstream data collected for unknown visitors to profiles established for known visitor IDs. The features are selected based on analysis that accounts for consistency, completeness, and uniqueness of features among a corpus of profiles. Then, relevance scores are computed over the selected features using an information retrieval model in which clickstreams are treated as queries and profiles are treated as documents. Unknown visitors are matched to corresponding profiles using the relevance scores. Access to the digital media content is then controlled in accordance with the matching based on relevance scores, such as by serving individualized marketing offers and content to consumers that is targeted to characteristics of the consumers indicated by respective profiles.

公开(公告)号：US20200372399A1

公开(公告)日：2020-11-26

申请号：US16419676

申请日：2019-05-22

Applicant: Adobe Inc.

Inventor： Tak Yeon Lee ,  Jonggi Hong ,  Eunyee Koh

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

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：US20200033144A1

公开(公告)日：2020-01-30

申请号：US16047908

申请日：2018-07-27

Applicant: Adobe Inc.

Inventor： Fan Du ,  Sana Malik Lee ,  Georgios Theocharous ,  Eunyee Koh

IPC: G01C21/34 ,  G06Q10/04 ,  H04W4/021 ,  H04W4/024

Abstract: The present disclosure relates to generating and modifying recommended event sequences utilizing a dynamic user preference interface. For example, in one or more embodiments, the system generates a recommended event sequence using a recommendation model trained based on a plurality of historical event sequences. The system then provides, for display via a client device, the recommendation, a plurality of interactive elements for entry of user preferences, and a visual representation of historical event sequences. Upon detecting input of user preferences, the system can modify a reward function of the recommendation model and provide a modified recommended event sequence together with the plurality of interactive elements. In one or more embodiments, as a user enters user preferences, the system additionally modifies the visual representation to display subsets of the plurality of historical event sequences corresponding to the preferences.

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：US20240163238A1

公开(公告)日：2024-05-16

申请号：US18055238

申请日：2022-11-14

Applicant: Adobe Inc.

Inventor： Yeuk-yin Chan ,  Andrew Thomson ,  Caroline Kim ,  Cole Connelly ,  Eunyee Koh ,  Michelle Lee ,  Shunan Guo

IPC: H04L51/07 ,  G06F3/04842

CPC classification number: H04L51/07 ,  G06F3/04842

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates editable email components by utilizing an Answer Set Programming (ASP) model with hard and soft constraints. For instance, in one or more embodiments, the disclosed systems generate editable email components from email fragments of an email file utilizing an Answer Set Programming (ASP) model. In particular, the disclosed systems extract facts for the ASP model from the email file. In addition, the disclosed systems determine rows or columns defining cells of the email file utilizing ASP hard constraints defined by a first set of ASP atoms corresponding to the facts. Moreover, the disclosed systems determine editable email component classes for the email fragments utilizing ASP soft constraints defined by ASP classification weights and a second set of ASP atoms corresponding to the facts.

公开(公告)号：US11860675B2

公开(公告)日：2024-01-02

申请号：US17373281

申请日：2021-07-12

Applicant: ADOBE INC.

Inventor： Di Jin ,  Ryan A. Rossi ,  Eunyee Koh ,  Sungchul Kim ,  Anup Rao

IPC: G06F16/24 ,  G06F16/2458 ,  G06F16/901 ,  G06F16/26 ,  G06F16/215 ,  G06F16/28

CPC classification number: G06F16/2465 ,  G06F16/215 ,  G06F16/26 ,  G06F16/288 ,  G06F16/9024 ,  G06F2216/03

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for latent summarization of a graph. Structural features can be captured from feature vectors associated with each node of the graph by applying base functions on the feature vectors and iteratively applying relational operators to successive feature matrices to derive deeper inductive relational functions that capture higher-order structural information in different subgraphs of increasing size (node separations). Heterogeneity can be summarized by performing capturing features in appropriate subgraphs (e.g., node-centric neighborhoods associated with each node type, edge direction, and/or edge type). Binning and/or dimensionality reduction can be applied to the resulting feature matrices. The resulting set of relational functions and multi-level feature matrices can form a latent summary that can be used to perform a variety of graph-based tasks, including node classification, node clustering, link prediction, entity resolution, anomaly and event detection, and inductive learning tasks.

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：US20230386143A1

公开(公告)日：2023-11-30

申请号：US17664972

申请日：2022-05-25

Applicant: ADOBE INC.

Inventor： Chang Xiao ,  Ryan A. Rossi ,  Eunyee Koh

IPC: G06T19/00 ,  G06T7/00 ,  G06T7/73

CPC classification number: G06T19/006 ,  G06T7/97 ,  G06T7/73 ,  G06T2207/30204 ,  G06T2207/20224

Abstract: A system and methods for providing human-invisible AR markers is described. One aspect of the system and methods includes identifying AR metadata associated with an object in an image; generating AR marker image data based on the AR metadata; generating a first variant of the image by adding the AR marker image data to the image; generating a second variant of the image by subtracting the AR marker image data from the image; and displaying the first variant and the second variant of the image alternately at a display frequency to produce a display of the image, wherein the AR marker image data is invisible to a human vision system in the display of the image.