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公开(公告)号:US10789411B2
公开(公告)日:2020-09-29
申请号:US16025140
申请日:2018-07-02
Applicant: Adobe Inc.
Inventor: Balaji Vasan Srinivasan , Vishwa Vinay , Niyati Chhaya , Cedric Huesler
IPC: G06F40/106 , G06F40/186 , G06F40/14
Abstract: The present disclosure includes systems, methods, and non-transitory computer readable media that utilize a genetic framework to generate enhanced digital layouts from digital content fragments. In particular, in one or more embodiments, the disclosed systems iteratively generate a layout chromosome of digital content fragments, determine a fitness level of the layout chromosome, and mutate the layout chromosome until converging to an improved fitness level. The disclosed systems can efficiently utilize computing resources to generate a digital layout from a layout chromosome that is optimized to specified platforms, distribution audiences, and target optimization goals.
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公开(公告)号:US10389679B2
公开(公告)日:2019-08-20
申请号:US16152107
申请日:2018-10-04
Applicant: Adobe Inc.
Inventor: Niyati Chhaya , Laurie M. Byrum , Harsh Jhamtani , Calvin K. C. Wong
Abstract: Techniques and systems are described to determine levels of competency of users as part of an online community and control generation of subsequent digital content to be used interaction of the online community with the users based on this determination. In one example, determination of the level of competency is based on relevance to topics of the online community. In another example, a determination is made as to whether the topic of the online community is stable before using user competency scores to control generation of subsequent digital content. In a further example, users of the online community are identified as exhibiting dormant or non-dormant behavior and used as a basis to control generation of subsequent digital content. In yet another example, user competency scores are adjusted based on a decay factor to address dormancy of users over a period of time.
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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:US20190087838A1
公开(公告)日:2019-03-21
申请号:US16196784
申请日:2018-11-20
Applicant: ADOBE INC.
Inventor: Niyati Chhaya , Kokil Jaidka
Abstract: Embodiments of the present invention relate to a determination of a user's exclusiveness toward a particular brand. User-specific entities are extracted from social media content associated with a user. At least a portion of the user-specific entities are brand-related entities that are specifically relevant to a particular brand. These brand-related entities are analyzed with respect to the user-specific entities extracted from the social media content to determine a level of exclusivity of the user to the brand.
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公开(公告)号:US10733359B2
公开(公告)日:2020-08-04
申请号:US15248675
申请日:2016-08-26
Applicant: ADOBE INC.
Inventor: Balaji Vasan Srinivasan , Rishiraj Saha Roy , Niyati Chhaya , Natwar Modani , Harsh Jhamtani
IPC: G06F40/131 , G06F16/335 , G06F40/169 , G06F40/284
Abstract: Systems and methods provide for expanding user-provided content. User-provided input content is received via a user interface. Content that is relevant to the user-provided input content is identified from a repository of previously-generated content. The identified relevant content is divided into content sub-segments. From the content sub-segments, one or more pieces of candidate content are identified based on each content sub-segment's relevance to the received input content. At least one piece of identified candidate content is provided for display. A selection of one or more pieces of identified candidate content is received, such that the selected piece(s) of identified candidate content is appended to the received input content, thereby expanding the user-provided content.
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公开(公告)号:US10733247B2
公开(公告)日:2020-08-04
申请号:US15046995
申请日:2016-02-18
Applicant: Adobe Inc.
Inventor: Payal Bajaj , Niyati Chhaya , Harsh Jhamtani , Shriram Venkatesh Shet Revankar , Anandhavelu N
IPC: G06F16/9535 , G06Q30/02
Abstract: Disclosed are various embodiments for automatically creating on a computer analytics tags for different object types of website objects in web pages with analytics tracking capability in a dynamic tag management system. In one implementation, user input is received identifying a website object for tagging in the web pages and keywords are identified based on the user input. Based on the keywords, multiple occurrences of the website object in the web are identified, wherein the multiple occurrences of the website object correspond to multiple object types. The computer automatically creates analytics tags for the website object corresponding to object types. Based on the website object, an expansion object is identified and the computer automatically creates an analytics tag for the expansion object.
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公开(公告)号:US10296546B2
公开(公告)日:2019-05-21
申请号:US14551365
申请日:2014-11-24
Applicant: Adobe Inc.
Inventor: Niyati Chhaya , Deepak Pai , Dhwanit Agarwal , Nikaash Puri , Paridhi Jain , Ponnurangam Kumaraguru
IPC: G06F16/00 , G06F16/9535 , H04L29/08 , G06F16/435 , G06F16/335
Abstract: Techniques are disclosed for identifying the same online user across different communication networks, and further creating a unified profile for that user. The unified profile is an aggregation of publicly available user profile attributes across the different networks. In an embodiment, the techniques are implemented as a computer implemented methodology, including: (1) feature space analysis to identify relevant user features that allows for clusterization of the given target network(s), (2) unsupervised candidate selection to identify one or more candidate user profiles from each target network and that are likely belonging to a target user or so-called queried user, and (3) supervised user identification to identify a likely matching user profile for that target user from each target network. A unified user profile can then be built from data taken from all matched user profiles, and effectively allows a marketer to better understand that user and hence execute more informed targeting.
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公开(公告)号:US20230020886A1
公开(公告)日:2023-01-19
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
IPC: G06F16/34 , G06F16/332 , G06N3/04 , 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:US20220129621A1
公开(公告)日:2022-04-28
申请号:US17079681
申请日:2020-10-26
Applicant: Adobe Inc.
Inventor: Bhanu Prakash Reddy Guda , Niyati Chhaya , Aparna Garimella
IPC: G06F40/166 , G10L25/63 , G06N20/00 , G06K9/62
Abstract: Certain embodiments involve using machine-learning tools that include Bidirectional Encoder Representations from Transformers (“BERT”) language models for predicting emotional responses to text by, for example, target readers having certain demographics. For instance, a machine-learning model includes, at least, a BERT encoder and a classification module that is trained to predict demographically specific emotional responses. The BERT encoder encodes the input text into an input text vector. The classification module generates, from the input text vector and an input demographics vector representing a demographic profile of the reader, an emotional response score.
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公开(公告)号:US10984172B2
公开(公告)日:2021-04-20
申请号:US17008570
申请日:2020-08-31
Applicant: Adobe Inc.
Inventor: Balaji Vasan Srinivasan , Vishwa Vinay , Niyati Chhaya , Cedric Huesler
IPC: G06F40/106 , G06F40/186 , G06F40/14
Abstract: The present disclosure includes systems, methods, and non-transitory computer readable media that utilize a genetic framework to generate enhanced digital layouts from digital content fragments. In particular, in one or more embodiments, the disclosed systems iteratively generate a layout chromosome of digital content fragments, determine a fitness level of the layout chromosome, and mutate the layout chromosome until converging to an improved fitness level. The disclosed systems can efficiently utilize computing resources to generate a digital layout from a layout chromosome that is optimized to specified platforms, distribution audiences, and target optimization goals.
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