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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.
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公开(公告)号：US12045272B2
公开(公告)日：2024-07-23
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
CPC classification number: G06F16/345 , G06F16/3329 , G06F40/30 , G06N3/04 , G06N3/044 , 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.
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公开(公告)号：US12020195B2
公开(公告)日：2024-06-25
申请号：US17474188
申请日：2021-09-14
Applicant: Adobe Inc.
Inventor： Sana Malik Lee , Zhuohao Zhang , Zhicheng Liu , Tak Yeon Lee , Shunan Guo , Ryan A. Rossi , Fan Du , Eunyee Koh
IPC: G06T11/60 , G06N20/00 , G06Q10/0639 , G06T11/20
CPC classification number: G06Q10/0639 , G06N20/00 , G06T11/206 , G06T11/60
Abstract: In implementations of systems for generating interactive reports, a computing device implements a report system to receive input data describing a dataset and an analytics report for the dataset that depicts a result of performing analytics on the dataset. The report system generates a declarative specification that describes the analytics report in a language that encodes data as properties of graphic objects. Editing data is received describing a user input specifying a modification to the analytics report. The report system modifies the declarative specification using the language that encodes data as properties of graphic objects based on the user input and the dataset. An interactive report is generated based on the modified declarative specification that includes the analytics report having the modification.
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公开(公告)号：US11995547B2
公开(公告)日：2024-05-28
申请号：US17823390
申请日：2022-08-30
Applicant: Adobe Inc.
Inventor： Fan Du , Sungchul Kim , Shunan Guo , Sana Lee , Eunyee Koh
Abstract: Disclosed systems and methods predict and visualize outcomes based on past events. For example, an analysis application encodes a sequence of events into a feature vector that includes, for each event, a numerical representation of a respective category and a respective timestamp. The application applies a time-aware recurrent neural network to the feature vector, resulting in one or more of (i) a set of future events in which each event is associated with a probability and a predicted duration and (ii) a sequence embedding that contains information about predicted outcomes and temporal patterns observed in the sequence of events. The application applies a support vector model classifier to the sequence embedding. The support vector model classifier computes a likelihood of a categorical outcome for each of the events in the probability distribution. The application modifies interactive content according to the categorical outcomes and probability distribution.
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公开(公告)号：US11947545B2
公开(公告)日：2024-04-02
申请号：US17685223
申请日：2022-03-02
Applicant: ADOBE INC.
Inventor： Jonathan Ko , Ayush Tyagi , Fan Du , Yi Jin , Keshav Vadrevu
IPC: G06F16/00 , G06F16/2455
CPC classification number: G06F16/24568
Abstract: Systems and methods for configuring data stream filtering are disclosed. In one embodiment, a method for data stream processing comprises receiving an incoming dataset stream at a data stream processing environment, wherein the dataset stream comprises a data stream; configuring with a streaming data filter configuration tool, one or more filter parameters for a data filter that receives the data stream; computing with the streaming data filter configuration tool, one or more filter statistics estimates based on the filter parameters, wherein the filter statistics estimates are computed from sample elements of a representative sample of the data stream retrieved from a representative sample data store; outputting to a workstation user interface the filter statistics estimates; and configuring the data filter to apply the filter parameters to the data stream in response to an instruction from the workstation user interface.
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Patent Agency Ranking
56.发明授权公开(公告)号：US11946753B2
公开(公告)日：2024-04-02
申请号：US17364480
申请日：2021-06-30
Applicant: Adobe Inc.
Inventor： Fan Du , Sana Malik Lee , Georgios Theocharous , Eunyee Koh
IPC: H04W4/024 , G01C21/34 , G06Q10/047 , H04W4/021
CPC classification number: G01C21/343 , G01C21/3476 , G01C21/3484 , G06Q10/047 , 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.
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公开(公告)号：US11775756B2
公开(公告)日：2023-10-03
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 , G06F40/58 , G06F40/169 , G06F40/56 , G06F40/295
CPC classification number: G06F40/216 , G06F40/169 , G06F40/295 , G06F40/56 , G06F40/58
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.
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公开(公告)号：US20230267132A1
公开(公告)日：2023-08-24
申请号：US17677323
申请日：2022-02-22
Applicant: Adobe Inc.
Inventor： Yeuk-yin Chan , Tung Mai , Ryan Rossi , Moumita Sinha , Matvey Kapilevich , Margarita Savova , Fan Du , Charles Menguy , Anup Rao
IPC: G06F16/28
CPC classification number: G06F16/285
Abstract: A cluster generation system identifies data elements, from a first binary record, that each have a particular value and correspond to respective binary traits. A candidate description function describing the binary traits is generated, the candidate description function including a model factor that describes the data elements. Responsive to determining that a second record has additional data elements having the particular value and corresponding to the respective binary traits, the candidate description function is modified to indicate that the model factor describes the additional elements. The candidate description function is also modified to include a correction factor describing an additional binary trait excluded from the respective binary traits. Based on the modified candidate description function, the cluster generation system generates a data summary cluster, which includes a compact representation of the binary traits of the data elements and additional data elements.
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公开(公告)号：US20230130778A1
公开(公告)日：2023-04-27
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: G06F16/738 , G06F16/901 , G06F16/783 , G06F16/34 , G06F16/9032 , G06F16/44
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.
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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.
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