Patents by Inventor Himani Shukla
Himani Shukla 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: 11966954Abstract: A system comprising a database and a computing device. The database may be configured to store, sort and retrieve for each of a plurality of users a unique account and comments associated with the unique account. The computing device may be configured to display comments retrieved from the database associated with the unique account, generate an identification code to enable a commenter to add the comments to the unique account and communicate the comments to the database. The comments may comprise positive feedback about the users. The identification code may enable the commenter to add the comments without being one of the users. The comments may be displayed in response to an approval by the user of the unique account. The positive feedback may comprise a personalized message by the commenter about a performance of one of the users.Type: GrantFiled: March 28, 2022Date of Patent: April 23, 2024Inventors: Upendra Patel, Himani Shukla
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Publication number: 20230306070Abstract: Systems and methods for generating an output representation are disclosed. A system may include a processor including a representation generator. The representation generator may receive an input data comprising an input content and an instruction. The representation generator may include a parsing engine to parse the input data to obtain parsed information. The representation generator include a mapping engine to map the parsed information with a pre-stored base template pertaining to a pre-defined module, to obtain a mapped template. The representation generator may generate, through a machine learning (ML) model, based on the mapped template, an output representation in a pre-defined format. The output representation may correspond to the expected representation of the input content.Type: ApplicationFiled: March 24, 2022Publication date: September 28, 2023Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Swati TATA, Ditty MATHEW, Srivasan SRIDHARAN, Himani SHUKLA, Chinnappa GUGGILLA, Kamlesh Narayan CHAUDHARI, Divyayan DEY
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Publication number: 20230079369Abstract: A system comprising a database and a computing device. The database may be configured to store, sort and retrieve for each of a plurality of users a unique account and comments associated with the unique account. The computing device may be configured to display comments retrieved from the database associated with the unique account, generate an identification code to enable a commenter to add the comments to the unique account and communicate the comments to the database. The comments may comprise positive feedback about the users. The identification code may enable the commenter to add the comments without being one of the users. The comments may be displayed in response to an approval by the user of the unique account. The positive feedback may comprise a personalized message by the commenter about a performance of one of the users.Type: ApplicationFiled: March 28, 2022Publication date: March 16, 2023Inventors: Upendra Patel, Himani Shukla
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Patent number: 11556610Abstract: Examples of a content alignment system are provided. The system may receive a content record and a content creation requirement. The system may implement an artificial intelligence component to sort the content record into a plurality of objects and for identifying an object boundary for each of the plurality of objects. The system may identify a plurality of images and implement a first cognitive learning operation to identify an image boundary for each of the plurality of images. The system may identify a plurality of exhibits and implement a second cognitive learning operation to identify a data pattern associated with each of the plurality of exhibits. The system may implement a third cognitive learning operation for determining a content creation model by evaluating the plurality of objects, the plurality of images, and the plurality of exhibits. The system may generate a content creation output to resolve the content creation requirement.Type: GrantFiled: November 8, 2019Date of Patent: January 17, 2023Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Pratip Samanta, Manash Jyoti Konwar, Keshav Bohra, Himani Shukla, Nagendra Kumar Karamala, Madhura Shivaram, Amit Sharma, Sumeet Sawarkar, Swati Tata
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Publication number: 20210142356Abstract: Examples of a content alignment system are provided. The system may receive a content record and a content creation requirement. The system may implement an artificial intelligence component to sort the content record into a plurality of objects and for identifying an object boundary for each of the plurality of objects. The system may identify a plurality of images and implement a first cognitive learning operation to identify an image boundary for each of the plurality of images. The system may identify a plurality of exhibits and implement a second cognitive learning operation to identify a data pattern associated with each of the plurality of exhibits. The system may implement a third cognitive learning operation for determining a content creation model by evaluating the plurality of objects, the plurality of images, and the plurality of exhibits. The system may generate a content creation output to resolve the content creation requirement.Type: ApplicationFiled: November 8, 2019Publication date: May 13, 2021Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Pratip SAMANTA, Manash JYOTI KONWAR, Keshav BOHRA, Himani SHUKLA, Nagendra Kumar KARAMALA, Madhura SHIVARAM, Amit SHARMA, Sumeet SAWARKAR, Swati TATA
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Patent number: 10997507Abstract: A system for reconciliation comprises a determination engine to determine whether data is structured or unstructured, a data structuring engine to structure the data, and a rule extraction engine to determine relations between pairs of values of a first set and a second set of data. The system further comprises a matching engine to generate a confidence score for each pair of the values, a categorization engine to classify the pairs of values into matched pairs and unmatched pairs, a validation engine to validate matching and classification of the pairs based on a user feedback, and a learning engine to store details pertaining to the validation of the matching and the classification over a period of time. The learning engine forwards the details to the rule extraction engine and the categorization engine to determine the relations between subsequent pairs of values and classify the pairs based on the stored details.Type: GrantFiled: June 1, 2017Date of Patent: May 4, 2021Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Srikrishna Raamadhurai, Abhishek Datta Sharma, Siddhartha Asthana, Suresh Venkatasubramaniyan, Himani Shukla, Madhura Shivaram, Chung-Sheng Li
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Publication number: 20180349776Abstract: A system for reconciliation comprises a determination engine to determine whether data is structured or unstructured, a data structuring engine to structure the data, and a rule extraction engine to determine relations between pairs of values of a first set and a second set of data. The system further comprises a matching engine to generate a confidence score for each pair of the values, a categorization engine to classify the pairs of values into matched pairs and unmatched pairs, a validation engine to validate matching and classification of the pairs based on a user feedback, and a learning engine to store details pertaining to the validation of the matching and the classification over a period of time. The learning engine forwards the details to the rule extraction engine and the categorization engine to determine the relations between subsequent pairs of values and classify the pairs based on the stored details.Type: ApplicationFiled: June 1, 2017Publication date: December 6, 2018Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Srikrishna RAAMADHURAI, Abhishek Datta Sharma, Siddhartha Asthana, Suresh Venkatasubramaniyan, Himani Shukla, Madhura Shivaram, Chung-Sheng Li