Patents by Inventor Jayatu Sen Chaudhury
Jayatu Sen Chaudhury 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: 12045571Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.Type: GrantFiled: November 8, 2022Date of Patent: July 23, 2024Assignee: AMERICAN EXPRESS TRAVEL RELATED SERVICES COMPANY, INC.Inventors: Prodip Hore, Mrigank Prince, Jayatu Sen Chaudhury, Prakhar Thapak, Soham Banerjee, Shailja Pandey, Chanderpreet Singh Duggal
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Publication number: 20230177270Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.Type: ApplicationFiled: November 8, 2022Publication date: June 8, 2023Applicant: American Express Travel Related Services Company, Inc.Inventors: Prodip HORE, Mrigank PRINCE, Jayatu Sen CHAUDHURY, Prakhar THAPAK, Soham BANERJEE, Shailja PANDEY, Chanderpreet Singh DUGGAL
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Patent number: 11625535Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.Type: GrantFiled: December 5, 2019Date of Patent: April 11, 2023Assignee: American Express Travel Related Services Company, Inc.Inventors: Prodip Hore, Mrigank Prince, Jayatu Sen Chaudhury, Prakhar Thapak, Soham Banerjee, Shailja Pandey, Chanderpreet Singh Duggal
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Patent number: 11514243Abstract: At least some embodiments are directed to an entity classification system receives informational data associated with an entity. The informational data includes sentences associated with the entity. The entity classification system utilizes a first machine learning model to determine a first contextual meaning among words of a sentence associated with the entity based on a first word embedding technique, and determines at least one category associated with the entity based at least in part on the first contextual meaning. The entity classification system utilizes a second machine learning model to determine a second contextual meaning shared by a set of sentences based on a second embedding technique, and determines a subcategory of the category associated with the entity based at least in part on the second contextual meaning. The entity classification system generates an output including the category and subcategory associated with the entity.Type: GrantFiled: December 5, 2019Date of Patent: November 29, 2022Assignee: American Express Travel Related Services Company, Inc.Inventors: Prodip Hore, Mrigank Prince, Jayatu Sen Chaudhury, Prakhar Thapak, Soham Banerjee, Shailja Pandey, Chanderpreet Singh Duggal
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Publication number: 20210073669Abstract: Disclosed are various embodiments for generating training data for machine-learning models. A plurality of original records are analyze to identify a probability distribution function (PDF), wherein a sample space of the PDF comprises the plurality of original records. A plurality of new records are generated using the PDF. An augmented dataset that includes the plurality of new records is created. Then, a machine-learning model is trained using the augmented dataset.Type: ApplicationFiled: September 6, 2019Publication date: March 11, 2021Inventors: Soham Banerjee, Jayatu Sen Chaudhury, Prodip Hore, Rohit Joshi, Snehansu Sekhar Sahu
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Publication number: 20190385170Abstract: The system may be configured to perform operations including receiving a transaction authorization request comprising transaction details; inputting the transaction details into a fraud scoring system comprising a fixed fraud detection model; inputting the transaction details into a neural network comprising an improvable fraud detection model; applying the fixed fraud detection model and the improvable fraud detection model to the transaction details; producing a fraud score in response to applying the fixed fraud detection model to the transaction details and a neural network fraud score in response to applying the improvable fraud detection model to the transaction details; analyzing the fraud score and the neural network fraud score; and/or sending an authorization response in response to analyzing the fraud score and the neural network fraud score.Type: ApplicationFiled: June 19, 2018Publication date: December 19, 2019Applicant: American Express Travel Related Services Company, Inc.Inventors: Apoorv Reddy Arrabothu, Jayatu Sen Chaudhury, Prodip Hore, Avinash Tripathy, Di Xu
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Patent number: 7912795Abstract: Predictive models are developed automatically for a plurality of modeling variables. The plurality of modeling variables is transformed, based on a transformation rule. A clustering of the transformed modeling variables is performed to create variable clusters. A set of variables is selected from the variable clusters based on a selection rule. A regression of the set of variables is performed to determine prediction variables. The prediction variables are utilized in developing a predictive model. The development of the predictive model may include modification of the predictive model, review of the plurality of transformations, and validation of the predictive model.Type: GrantFiled: April 7, 2010Date of Patent: March 22, 2011Assignee: American Express Travel Related services Company, Inc.Inventors: Jayatu Sen Chaudhury, Amber Gupta, Prasanta Sahu, Tirthankar Choudhuri
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Publication number: 20100198762Abstract: Predictive models are developed automatically for a plurality of modeling variables. The plurality of modeling variables is transformed, based on a transformation rule. A clustering of the transformed modeling variables is performed to create variable clusters. A set of variables is selected from the variable clusters based on a selection rule. A regression of the set of variables is performed to determine prediction variables. The prediction variables are utilized in developing a predictive model. The development of the predictive model may include modification of the predictive model, review of the plurality of transformations, and validation of the predictive model.Type: ApplicationFiled: April 7, 2010Publication date: August 5, 2010Applicant: AMERICAN EXPRESS TRAVEL RELATED SERVICES COMPANY, INC.Inventors: Jayatu Sen Chaudhury, Amber Gupta, Prasanta Sahu, Tirthankar Choudhuri
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Patent number: 7720782Abstract: Predictive models are developed automatically for a plurality of modeling variables. The plurality of modeling variables is transformed, based on a transformation rule. A clustering of the transformed modeling variables is performed to create variable clusters. A set of variables is selected from the variable clusters based on a selection rule. A regression of the set of variables is performed to determine prediction variables. The prediction variables are utilized in developing a predictive model. The development of the predictive model may include modification of the predictive model, review of the plurality of transformations, and validation of the predictive model.Type: GrantFiled: December 22, 2006Date of Patent: May 18, 2010Assignee: American Express Travel Related Services Company, Inc.Inventors: Jayatu Sen Chaudhury, Amber Gupta, Prasanta Sahu, Tirthankar Choudhuri
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Publication number: 20080154814Abstract: Predictive models are developed automatically for a plurality of modeling variables. The plurality of modeling variables is transformed, based on a transformation rule. A clustering of the transformed modeling variables is performed to create variable clusters. A set of variables is selected from the variable clusters based on a selection rule. A regression of the set of variables is performed to determine prediction variables. The prediction variables are utilized in developing a predictive model. The development of the predictive model may include modification of the predictive model, review of the plurality of transformations, and validation of the predictive model.Type: ApplicationFiled: December 22, 2006Publication date: June 26, 2008Applicant: American Express Travel Related Services Company, Inc.Inventors: Jayatu Sen Chaudhury, Amber Gupta, Prasanta Sahu, Tirthankar Choudhuri