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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.
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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
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.
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公开(公告)号：US11829940B2
公开(公告)日：2023-11-28
申请号：US18117586
申请日：2023-03-06
Applicant: Adobe Inc.
Inventor： Kirankumar Shiragur , Tung Thanh Mai , Anup Bandigadi Rao , Ryan A. Rossi , Georgios Theocharous , Michele Saad
IPC: G06Q10/0835 , G06Q10/087 , G06Q10/047 , G06F17/11
CPC classification number: G06Q10/08355 , G06F17/11 , G06Q10/047 , G06Q10/087
Abstract: In implementations of item transfer control systems, a computing device implements a transfer system to receive input data describing types of requested items and corresponding quantities of the types of requested items to receive at each of a plurality of destination sites and types of available items and corresponding quantities of the types of available items that are available at each of a plurality of source sites. The transfer system constructs a flow network having a source node for each of the plurality of the source sites and a destination node for each of the plurality of the destination sites. An integral approximate solution is generated that transfers the corresponding quantities of the types of requested items to each of the plurality of the destination sites using a maximum flow solver and the flow network. The transfer system causes transferences of the corresponding quantities of the types of requested items to each of the plurality of the destination sites based on the integral approximate solution.
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公开(公告)号：US20230153338A1
公开(公告)日：2023-05-18
申请号：US17527001
申请日：2021-11-15
Applicant: ADOBE INC.
Inventor： Tung Mai , Saayan Mitra , Ryan A. Rossi , Gaurav Gupta , Anup Rao , Xiang Chen
CPC classification number: G06F16/3338 , G06F16/325 , G06F16/319 , G06F16/3347
Abstract: A search system facilitates efficient and fast near neighbor search given item vector representations of items, regardless of item type or corpus size. To index an item, the search system expands an item vector for the item to generate an expanded item vector and selects elements of the expanded item vector. The item is index by storing an identifier of the item in posting lists of an index corresponding to the position of each selected element in the expanded item vector. When a query is received, a query vector for the item is expanded to generate an expanded query vector, and elements of the expanded query vector are selected. Candidate items are identified based on posting lists corresponding to the position of each selected element in the expand query vector. The candidate items may be ranked, and a result set is returned as a response to the query.
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公开(公告)号：US11621892B2
公开(公告)日：2023-04-04
申请号：US17095070
申请日：2020-11-11
Applicant: Adobe Inc.
Inventor： Sungchul Kim , Di Jin , Ryan A. Rossi , Eunyee Koh
IPC: H04L41/12 , H04L43/067 , G06F16/901 , H04L41/14 , H04L43/045
Abstract: Deriving network embeddings that represent attributes of, and relationships between, different nodes in a network while preserving network data temporal and structural properties is described. A network representation system generates a plurality of graph time-series representations of network data that each includes a subset of nodes and edges included in a time segment of the network data, constrained either by time or a number of edges included in the representation. A temporal graph of the network data is generated by implementing a temporal model that incorporates temporal dependencies into the graph time-series representations. From the temporal graph, network embeddings for the network data are derived, where the network embeddings capture temporal dependencies between nodes, as indicated by connecting edges, as well as temporal structural properties of the network data. Network embeddings represent network data in a low-dimensional latent space, which is useable to generate a prediction regarding the network data.
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Patent Agency Ranking
公开(公告)号：US11593893B2
公开(公告)日：2023-02-28
申请号：US16677007
申请日：2019-11-07
Applicant: Adobe Inc.
Inventor： Ryan A. Rossi
IPC: G06Q50/00 , G06Q30/02 , G06Q30/0201 , G06Q30/0273 , G06Q30/0251
Abstract: In implementations of multi-item influence maximization, a computing device can obtain updates to a user association graph that indicates social correspondence between users, and obtain updates to a user-item graph that indicates user correspondence with one or more items. The computing device includes an influence maximization module that can update an item association graph that indicates item correspondence of each item with one or more other items, where the item association graph can be updated based on the user-item graph that indicates the user correspondence with one or more of the items. The influence maximization module can then iteratively determine a resource allocation for each of the users to maximize user influence of multiple items that are associated in the item association graph and based on the social correspondence between the users, as well as assign a variable portion of the resource allocation to any number of the users.
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公开(公告)号：US20230041594A1
公开(公告)日：2023-02-09
申请号：US17394707
申请日：2021-08-05
Applicant: Adobe Inc.
Inventor： Kirankumar Shiragur , Tung Thanh Mai , Anup Bandigadi Rao , Ryan A. Rossi , Georgios Theocharous , Michele Saad
Abstract: In implementations of item transfer control systems, a computing device implements a transfer system to receive input data describing types of requested items and corresponding quantities of the types of requested items to receive at each of a plurality of destination sites and types of available items and corresponding quantities of the types of available items that are available at each of a plurality of source sites. The transfer system constructs a flow network having a source node for each of the plurality of the source sites and a destination node for each of the plurality of the destination sites. An integral approximate solution is generated that transfers the corresponding quantities of the types of requested items to each of the plurality of the destination sites using a maximum flow solver and the flow network. The transfer system causes transferences of the corresponding quantities of the types of requested items to each of the plurality of the destination sites based on the integral approximate solution.
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公开(公告)号：US11487579B2
公开(公告)日：2022-11-01
申请号：US16867104
申请日：2020-05-05
Applicant: ADOBE INC.
Inventor： Kanak Vivek Mahadik , Ryan A. Rossi , Sana Malik Lee , Georgios Theocharous , Handong Zhao , Gang Wu , Youngsuk Park
Abstract: A system and method for automatically adjusting computing resources provisioned for a computer service or application by applying historical resource usage data to a predictive model to generate predictive resource usage. The predictive resource usage is then simulated for various service configurations, determining scaling requirements and resource wastage for each configuration. A cost value is generated based on the scaling requirement and resource wastage, with the cost value for each service configuration used to automatically select a configuration to apply to the service. Alternatively, the method for automatically adjusting computer resources provisioned for a service may include receiving resource usage data of the service, applying it to a linear quadratic regulator (LQR) to find an optimal stationary policy (treating the resource usage data as states and resource-provisioning variables as actions), and providing instructions for configuring the service based on the optimal stationary policy.
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公开(公告)号：US11461638B2
公开(公告)日：2022-10-04
申请号：US16296076
申请日：2019-03-07
Applicant: ADOBE INC.
Inventor： Sungchul Kim , Scott Cohen , Ryan A. Rossi , Charles Li Chen , Eunyee Koh
Abstract: Embodiments of the present invention are generally directed to generating figure captions for electronic figures, generating a training dataset to train a set of neural networks for generating figure captions, and training a set of neural networks employable to generate figure captions. A set of neural networks is trained with a training dataset having electronic figures and corresponding captions. Sequence-level training with reinforced learning techniques are employed to train the set of neural networks configured in an encoder-decoder with attention configuration. Provided with an electronic figure, the set of neural networks can encode the electronic figure based on various aspects detected from the electronic figure, resulting in the generation of associated label map(s), feature map(s), and relation map(s). The trained set of neural networks employs a set of attention mechanisms that facilitate the generation of accurate and meaningful figure captions corresponding to visible aspects of the electronic figure.
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公开(公告)号：US20220150123A1
公开(公告)日：2022-05-12
申请号：US17095070
申请日：2020-11-11
Applicant: Adobe Inc.
Inventor： Sungchul Kim , Di Jin , Ryan A. Rossi , Eunyee Koh
IPC: H04L12/24 , H04L12/26 , G06F16/901
Abstract: Deriving network embeddings that represent attributes of, and relationships between, different nodes in a network while preserving network data temporal and structural properties is described. A network representation system generates a plurality of graph time-series representations of network data that each includes a subset of nodes and edges included in a time segment of the network data, constrained either by time or a number of edges included in the representation. A temporal graph of the network data is generated by implementing a temporal model that incorporates temporal dependencies into the graph time-series representations. From the temporal graph, network embeddings for the network data are derived, where the network embeddings capture temporal dependencies between nodes, as indicated by connecting edges, as well as temporal structural properties of the network data. Network embeddings represent network data in a low-dimensional latent space, which is useable to generate a prediction regarding the network data.
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