Patents by Inventor Shagun Kush
Shagun Kush has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11604924Abstract: Techniques are provided herein for generating improved document summaries that consider the amount of time that has passed since the user last accessed the document. The length of time that has passed since the user has accessed each previous portion of the document is used as a variable to determine how much the summary should focus on each of the previously read sections of the document. When a document is accessed by a user, a relevance score is assigned to content from previously accessed sections of that document, where the relevance score is weighted based on how long ago each of the sections was accessed by the user. Once the various content items of previous sections have been provided relevance scores, selected sentences with the highest relevance scores are fed to a deep learning sequence-to-sequence model is used to build the document summary.Type: GrantFiled: January 13, 2021Date of Patent: March 14, 2023Assignee: Adobe, Inc.Inventors: Shagun Kush, Sachin Soni, Nikita Kapoor, Carl Iwan Dockhorn, Ashish Rawat, Ajay Jain, Abhishek Jain
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Publication number: 20220222439Abstract: Techniques are provided herein for generating improved document summaries that consider the amount of time that has passed since the user last accessed the document. The length of time that has passed since the user has accessed each previous portion of the document is used as a variable to determine how much the summary should focus on each of the previously read sections of the document. When a document is accessed by a user, a relevance score is assigned to content from previously accessed sections of that document, where the relevance score is weighted based on how long ago each of the sections was accessed by the user. Once the various content items of previous sections have been provided relevance scores, selected sentences with the highest relevance scores are fed to a deep learning sequence-to-sequence model is used to build the document summary.Type: ApplicationFiled: January 13, 2021Publication date: July 14, 2022Applicant: Adobe, Inc.Inventors: Shagun Kush, Sachin Soni, Nikita Kapoor, Carl Iwan Dockhorn, Ashish Rawat, Ajay Jain, Abhishek Jain
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Publication number: 20220172501Abstract: Techniques are disclosed for identifying asides within a document, and detecting a display order of contents based of the identified asides. In a document, an “aside” represents a content region of the document that is distinct from the main content regions, and may be visually distinguishable from the main content region. In an example, a document is received, where the document lacks identification of asides. The document is analyzed to identify asides within the document. A display order of contents within the document is then determined, based on the identified asides. For example, in the display order, the asides are ordered between two segments of the main content and/or at a beginning or an end of the main content, but may not be ordered to be embedded in between a segment of the main content. The document is displayed in accordance with the display order.Type: ApplicationFiled: February 17, 2022Publication date: June 2, 2022Applicant: Adobe Inc.Inventors: Sanjeev Tagra, Shawn Alan Gaither, Shagun Kush, Samarth Gupta, Sachin Soni, Nikolaos Barmpalios, Abhishek Jain, Naqushab Neyazee
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Publication number: 20220114624Abstract: Digital content text processing techniques are described. In one example, a text corpus is extracted from digital content and text corpus keywords are identified that are included in the text corpus. A plurality of clusters is formed based on the text corpus keywords. Cluster scores are generated for reviews that define a probability the review belongs to a respective cluster, e.g., based on review keywords extracted from the reviews. Sentiment values and sentiment weights are also generated. The sentiment values describe a sentiment that each of the reviews exhibits towards a respective cluster, e.g., a type of sentiment such as positive, neutral, or negative. The sentiment weights describe an amount of weight to be applied for each sentiment with respect to that cluster. The service provider system then generates ranking scores based on the cluster scores and the sentiment scores which are used to control output of the reviews.Type: ApplicationFiled: October 9, 2020Publication date: April 14, 2022Applicant: Adobe Inc.Inventors: Ajay Jain, Shagun Kush, Sanjeev Tagra, Sachin Soni, Ryan Timothy Rozich, Jonathan Stephen Roeder
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Patent number: 11256913Abstract: Techniques are disclosed for identifying asides within a document, and detecting a display order of contents based of the identified asides. In a document, an “aside” represents a content region of the document that is distinct from the main content regions, and may be visually distinguishable from the main content region. In an example, a document is received, where the document lacks identification of asides. The document is analyzed to identify asides within the document. A display order of contents within the document is then determined, based on the identified asides. For example, in the display order, the asides are ordered between two segments of the main content and/or at a beginning or an end of the main content, but may not be ordered to be embedded in between a segment of the main content. The document is displayed in accordance with the display order.Type: GrantFiled: October 10, 2019Date of Patent: February 22, 2022Assignee: Adobe Inc.Inventors: Sanjeev Tagra, Shawn Alan Gaither, Shagun Kush, Samarth Gupta, Sachin Soni, Nikolaos Barmpalios, Abhishek Jain, Naqushab Neyazee
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Publication number: 20210110151Abstract: Techniques are disclosed for identifying asides within a document, and detecting a display order of contents based of the identified asides. In a document, an “aside” represents a content region of the document that is distinct from the main content regions, and may be visually distinguishable from the main content region. In an example, a document is received, where the document lacks identification of asides. The document is analyzed to identify asides within the document. A display order of contents within the document is then determined, based on the identified asides. For example, in the display order, the asides are ordered between two segments of the main content and/or at a beginning or an end of the main content, but may not be ordered to be embedded in between a segment of the main content. The document is displayed in accordance with the display order.Type: ApplicationFiled: October 10, 2019Publication date: April 15, 2021Applicant: Adobe Inc.Inventors: Sanjeev Tagra, Shawn Alan Gaither, Shagun Kush, Samarth Gupta, Sachin Soni, Nikolaos Barmpalios, Abhishek Jain, Naqushab Neyazee