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公开(公告)号:US12061995B2
公开(公告)日:2024-08-13
申请号:US16813098
申请日:2020-03-09
Applicant: ADOBE INC.
Inventor: Trung Huu Bui , Tong Sun , Natwar Modani , Lidan Wang , Franck Dernoncourt
IPC: G06N7/01 , G06F40/205 , G06F40/279 , G06F40/30 , G06N20/00
CPC classification number: G06N7/01 , G06F40/205 , G06F40/279 , G06F40/30 , G06N20/00
Abstract: Methods for natural language semantic matching performed by training and using a Markov Network model are provided. The trained Markov Network model can be used to identify answers to questions. Training may be performed using question-answer pairs that include labels indicating a correct or incorrect answer to a question. The trained Markov Network model can be used to identify answers to questions from sources stored on a database. The Markov Network model provides superior performance over other semantic matching models, in particular, where the training data set includes a different information domain type relative to the input question or the output answer of the trained Markov Network model.
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公开(公告)号:US10762283B2
公开(公告)日:2020-09-01
申请号:US14947964
申请日:2015-11-20
Applicant: Adobe Inc.
Inventor: Natwar Modani , Vaishnavi Subramanian , . Utpal , Shivani Gupta , Pranav R. Maneriker , Gaurush Hiranandani , Atanu R. Sinha
IPC: G06F17/00 , G06F40/166 , G06F16/93 , G06F16/438 , G06F16/34 , G06N5/00 , G06N5/02 , G06F40/30 , G06N3/04 , G06N3/08
Abstract: Multimedia document summarization techniques are described. That is, given a document that includes text and a set of images, various implementations generate a summary by extracting relevant text segments in the document and relevant segments of images with constraints on the amount of text and number/size of images in the summary.
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公开(公告)号:US12198459B2
公开(公告)日:2025-01-14
申请号:US17534744
申请日:2021-11-24
Applicant: Adobe Inc.
Inventor: Natwar Modani , Vaidehi Ramesh Patil , Inderjeet Jayakumar Nair , Gaurav Verma , Anurag Maurya , Anirudh Kanfade
IPC: G06K9/34 , G06V30/19 , G06V30/262 , G06V30/413 , G06V30/414 , G06V30/418
Abstract: In implementations of systems for generating indications of relationships between electronic documents, a processing device implements a relationship system to segment text of electronic documents included in a document corpus into segments. The relationship system determines a subset of the electronic documents that includes electronic document pairs having a number of similar segments that is greater than a threshold number. The similar segments are identified using locality sensitive hashing. The electronic document pairs are classified as related documents or unrelated documents using a machine learning model that receives a pair of electronic documents as an input and generates an indication of a classification for the pair of electronic documents as an output. Indications of relationships between particular electronic documents included in the subset are generated based at least partially on the electronic document pairs that are classified as related documents.
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公开(公告)号:US12112349B2
公开(公告)日:2024-10-08
申请号:US15238208
申请日:2016-08-16
Applicant: ADOBE INC.
Inventor: Natwar Modani , Iftikhar Ahamath Burhanuddin , Gaurush Hiranandani , Shiv Kumar Saini
IPC: G06Q30/0242
CPC classification number: G06Q30/0244
Abstract: Methods and systems are provided herein for summarizing a set of anomalies corresponding to a group of metrics of interest to a monitoring system user. Initially, a set of anomalies corresponding to a group of metrics is identified as having values that are outside of a predetermined range. A correlation value is determined for at least a portion of pairs of anomalies in the set of anomalies. For each anomaly in the set of anomalies, an informativeness value is computed that indicates how informative each anomaly in the set of anomalies is to the monitoring system user. The correlation values and the informativeness values are then used to identify at least one key anomaly and a plurality of non-key anomalies from the set of anomalies. A summary is generated of the identified at least one key anomaly to provide information to the monitoring system user about the set of anomalies for a particular time period.
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公开(公告)号:US20230186667A1
公开(公告)日:2023-06-15
申请号:US17549270
申请日:2021-12-13
Applicant: ADOBE INC.
Inventor: Navita Goyal , Ani Nenkova Nenkova , Natwar Modani , Ayush Maheshwari , Inderjeet Jayakumar Nair
IPC: G06V30/413 , G06V30/416 , G06V10/26 , G06V10/74 , G06N20/00
CPC classification number: G06V30/413 , G06N20/00 , G06V10/26 , G06V10/761 , G06V30/416
Abstract: Techniques described herein are directed to assisting review of documents. In one embodiment, one or more text segments and one or more subjects in a document are identified. A text segment in the document is associated with a corresponding subject identified in the document. The text segment is classified with a content type value corresponding to a relation of the text segment to the corresponding subject. Thereafter, information is provided for the text segment associated with the corresponding subject for display on a user interface. Such information can include a representation of the content type value for the text segment.
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公开(公告)号:US11194958B2
公开(公告)日:2021-12-07
申请号:US16123966
申请日:2018-09-06
Applicant: Adobe Inc.
Inventor: Pranav Ravindra Maneriker , Vishwa Vinay , Sopan Khosla , Niyati Himanshu Chhaya , Natwar Modani , Cedric Huesler , Balaji Vasan Srinivasan , Anandha velu Natarajan
IPC: G06F40/10 , G06F40/166 , G06N20/00 , G06F40/30 , G06F40/109 , G06F40/103 , G06F40/253
Abstract: A fact replacement and style consistency tool is described. Rather than rely heavily on human involvement to replace facts and maintain consistent styles across multiple digital documents, the described change management system identifies factual and stylistic inconsistencies between these documents, in part, using natural language processing techniques. Once these inconsistencies are identified, the change management system generates a user interface that includes indications of the inconsistencies and information describing them, e.g., an indication noting not only a type of inconsistency but also presenting a first portion and at least a second portion of the multiple documents that are factually inconsistent. By automatically identifying these factual and stylistic inconsistencies across multiple documents and presenting indications of such cross-document inconsistencies, the described change management system eliminates human errors in connection with maintaining factual and stylistic consistency over a body of documents.
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公开(公告)号:US10949452B2
公开(公告)日:2021-03-16
申请号:US15854320
申请日:2017-12-26
Applicant: ADOBE INC.
Inventor: Balaji Vasan Srinivasan , Pranav Ravindra Maneriker , Natwar Modani , Kundan Krishna
IPC: G06F16/30 , G06F16/27 , G06F16/33 , G06F16/338 , G06F16/31 , G06F40/151 , G06F40/205 , G06F40/284
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitating corpus-based content generation, in particular, using graph-based multi-sentence compression to generate a final content output. In one embodiment, pre-existing source content is identified and retrieved from a corpus. The source content is then parsed into sentence tokens, mapped and weighted. The sentence tokens are further parsed into word tokens and weighted. The mapped word tokens are then compressed into candidate sentences to be used in a final content. The final content is assembled using ranked candidate sentences, such that the final content is organized to reduce information redundancy and optimize content cohesion.
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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:US11868714B2
公开(公告)日:2024-01-09
申请号:US17682911
申请日:2022-02-28
Applicant: ADOBE INC.
Inventor: Natwar Modani , Muskan Agarwal , Vishesh Kaushik , Aparna Garimella , Akhash N A , Garvit Bhardwaj , Manoj Kilaru , Priyanshu Agarwal
IPC: G06F17/00 , G06F40/186 , G06F40/284
CPC classification number: G06F40/186 , G06F40/284
Abstract: Methods and systems are provided for facilitating generation of fillable document templates. In embodiments, a document having a plurality of tokens is obtained. Using a machine learned model, a token state is identified for each token of the plurality of tokens. Each token state indicates whether a corresponding token is a static token that is to be included in a fillable document template or a dynamic token that is to be excluded in the fillable document template. Thereafter, a fillable document template corresponding with the document is generated, wherein for each dynamic token of the document, the fillable document template includes a fillable field corresponding to the respective dynamic token.
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公开(公告)号:US20230274084A1
公开(公告)日:2023-08-31
申请号:US17682911
申请日:2022-02-28
Applicant: ADOBE INC.
Inventor: Natwar Modani , Muskan Agarwal , Vishesh Kaushik , Aparna Garimella , Akhash N A , Garvit Bhardwaj , Manoj Kilaru , Priyanshu Agarwal
IPC: G06F40/186 , G06F40/284
CPC classification number: G06F40/186 , G06F40/284
Abstract: Methods and systems are provided for facilitating generation of fillable document templates. In embodiments, a document having a plurality of tokens is obtained. Using a machine learned model, a token state is identified for each token of the plurality of tokens. Each token state indicates whether a corresponding token is a static token that is to be included in a fillable document template or a dynamic token that is to be excluded in the fillable document template. Thereafter, a fillable document template corresponding with the document is generated, wherein for each dynamic token of the document, the fillable document template includes a fillable field corresponding to the respective dynamic token.
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