Patents by Inventor Ayush GUPTA
Ayush GUPTA 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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Publication number: 20240119045Abstract: Systems, devices, computer-implemented methods, and tangible non-transitory computer-readable media for generating reports from one or more databases that store disparate datasets are provided. Specifically, the proposed systems enable the intelligent generation of reports from multiple datasets by automatically determining a proposed set of join configurations for combination of the multiple datasets. Unique identifiers can be assigned to a portion of the combined dataset and the combined dataset can be expanded for performing an aggregation operation associated with the portion of the combined dataset by referencing the one or more unique identifiers. Reports can be generated based on the combined dataset and the aggregation operation.Type: ApplicationFiled: October 6, 2023Publication date: April 11, 2024Inventors: Nikunj Aggarwal, Utkarsh Bhatia, Kyle Michael Boston, Siddhartha Gunda, Abhishek Gupta, VenuMadhav Kattagoni, Himanshu Nanda, Ayush Rai
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Publication number: 20240119457Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant.Type: ApplicationFiled: October 6, 2023Publication date: April 11, 2024Applicant: MASTERCARD INTERNATIONAL INCORPORATEDInventors: Smriti Gupta, Adarsh Patankar, Akash Choudhary, Alekhya Bhatraju, Ammar Ahmad Khan, Amrita Kundu, Ankur Saraswat, Anubhav Gupta, Awanish Kumar, Ayush Agarwal, Brian M. McGuigan, Debasmita Das, Deepak Yadav, Diksha Shrivastava, Garima Arora, Gaurav Dhama, Gaurav Oberoi, Govind Vitthal Waghmare, Hardik Wadhwa, Jessica Peretta, Kanishk Goyal, Karthik Prasad, Lekhana Vusse, Maneet Singh, Niranjan Gulla, Nitish Kumar, Rajesh Kumar Ranjan, Ram Ganesh V, Rohit Bhattacharya, Rupesh Kumar Sankhala, Siddhartha Asthana, Soumyadeep Ghosh, Sourojit Bhaduri, Srijita Tiwari, Suhas Powar, Susan Skelsey
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Patent number: 11568856Abstract: A combination of propagation operations and learning algorithms is applied, using a selected set of labeled conversational logs retrieved from a subset of a plurality of conversational logs, to a remaining corpus of the plurality of conversational logs to train an automated response system according to an intent associated with each of the conversational logs. The combination of propagation operations and learning algorithms may include defining the labels by a user for the selected set of the subset of the plurality of conversational logs; training a probabilistic classifier using the defined labels of features of the selected set, wherein the probabilistic classifier produces labeling decisions for the subset of conversational logs; weighting the features of the selected set in a model optimization process; and/or training an additional classifier using the weighted features of the selected set and applying the additional classifier to the remaining corpus.Type: GrantFiled: October 21, 2020Date of Patent: January 31, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam Ho, Robert L. Yates, Blake McGregor, Rajendra G. Ugrani, Neil R. Mallinar, Abhishek Shah, Ayush Gupta
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Patent number: 11380306Abstract: Expansion of intent classification data utilizing batch utterance scheduling, by a processor in a computing environment. A set of unlabeled examples for intent processing is received by an intent builder iteratively defining an intent. The set of examples are separated into a first subset processed according to a first model and a second subset processed according to a second model. The first subset is incorporated into the intent builder during a building iteration and scheduling a first batch processing of the second subset processed according to the second model based on a scheduling criteria. The first batch processing of the second subset is initiated once the scheduling criteria is satisfied. Upon completion of the first batch processing, results of the completion are used to influence additional examples retrieved from the first subset and the second subset during a subsequent building iteration by the intent builder.Type: GrantFiled: October 31, 2019Date of Patent: July 5, 2022Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Neil Rohit Mallinar, Rajendra G Ugrani, Ayush Gupta
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Patent number: 11144727Abstract: Evaluating intent authoring processes, by a processor in a computing environment. A dataset comprising utterances of interactive dialog sessions between agents and clients for a given product or service is received. A classification of at least a portion of the utterances is performed for a target intent according to at least one of a plurality of recommendation algorithms, where the classification is performed by an automatic driver invoking the recommendation algorithm and simulating a manual confirmation of the algorithm's decision by a user. A classifier trained with the utterances recommended and confirmed by the automatic driver is automatically evaluated according to at least one of the plurality of evaluation criteria. A report tracking the evaluation results is generated.Type: GrantFiled: May 20, 2019Date of Patent: October 12, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam Ho, Abhishek Shah, Neil Mallinar, Rajendra G. Ugrani, Ayush Gupta
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Patent number: 11106875Abstract: Evaluating intent authoring processes, by a processor in a computing environment. Results are received of a simulated intent labeling effort of a dataset comprising utterances of interactive dialog sessions between agents and clients for a given product or service. Figures of merits for respective algorithms used to perform the simulated intent labeling effort are computed. Each of the respective algorithms are evaluated according to the computed figures of merits; and one of the respective algorithms is implemented for labeling intents of a remaining corpus of the synthesized dataset according to parameters evaluated in the computed figures of merits.Type: GrantFiled: May 20, 2019Date of Patent: August 31, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam Ho, Abhishek Shah, Neil Mallinar, Rajendra G. Ugrani, Ayush Gupta
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Publication number: 20210134273Abstract: Expansion of intent classification data utilizing batch utterance scheduling, by a processor in a computing environment. A set of unlabeled examples for intent processing is received by an intent builder iteratively defining an intent. The set of examples are separated into a first subset processed according to a first model and a second subset processed according to a second model. The first subset is incorporated into the intent builder during a building iteration and scheduling a first batch processing of the second subset processed according to the second model based on a scheduling criteria. The first batch processing of the second subset is initiated once the scheduling criteria is satisfied. Upon completion of the first batch processing, results of the completion are used to influence additional examples retrieved from the first subset and the second subset during a subsequent building iteration by the intent builder.Type: ApplicationFiled: October 31, 2019Publication date: May 6, 2021Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Neil Rohit MALLINAR, Rajendra G. UGRANI, Ayush GUPTA
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Publication number: 20210035557Abstract: A combination of propagation operations and learning algorithms is applied, using a selected set of labeled conversational logs retrieved from a subset of a plurality of conversational logs, to a remaining corpus of the plurality of conversational logs to train an automated response system according to an intent associated with each of the conversational logs. The combination of propagation operations and learning algorithms may include defining the labels by a user for the selected set of the subset of the plurality of conversational logs; training a probabilistic classifier using the defined labels of features of the selected set, wherein the probabilistic classifier produces labeling decisions for the subset of conversational logs; weighting the features of the selected set in a model optimization process; and/or training an additional classifier using the weighted features of the selected set and applying the additional classifier to the remaining corpus.Type: ApplicationFiled: October 21, 2020Publication date: February 4, 2021Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam HO, Robert L. YATES, Blake MCGREGOR, Rajendra G. UGRANI, Neil R. MALLINAR, Abhishek SHAH, Ayush GUPTA
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Publication number: 20200372111Abstract: Evaluating intent authoring processes, by a processor in a computing environment. A dataset comprising utterances of interactive dialog sessions between agents and clients for a given product or service is received. A classification of at least a portion of the utterances is performed for a target intent according to at least one of a plurality of recommendation algorithms, where the classification is performed by an automatic driver invoking the recommendation algorithm and simulating a manual confirmation of the algorithm's decision by a user. A classifier trained with the utterances recommended and confirmed by the automatic driver is automatically evaluated according to at least one of the plurality of evaluation criteria. A report tracking the evaluation results is generated.Type: ApplicationFiled: May 20, 2019Publication date: November 26, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam HO, Abhishek SHAH, Neil MALLINAR, Rajendra G. UGRANI, Ayush GUPTA
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Publication number: 20200372112Abstract: Evaluating intent authoring processes, by a processor in a computing environment. Results are received of a simulated intent labeling effort of a dataset comprising utterances of interactive dialog sessions between agents and clients for a given product or service. Figures of merits for respective algorithms used to perform the simulated intent labeling effort are computed. Each of the respective algorithms are evaluated according to the computed figures of merits; and one of the respective algorithms is implemented for labeling intents of a remaining corpus of the synthesized dataset according to parameters evaluated in the computed figures of merits.Type: ApplicationFiled: May 20, 2019Publication date: November 26, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam HO, Abhishek SHAH, Neil MALLINAR, Rajendra G. UGRANI, Ayush GUPTA
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Patent number: 10832659Abstract: Embodiments for training an automated response system using weak supervision and co-training in a computing environment are provided. A plurality of conversational logs comprising interactive dialog sessions between agents and clients for a given product or service are received. A subset of the plurality of conversational logs are retrieved according to a defined criterion, and a selected set of the subset of the plurality of retrieved conversational logs are labeled by a user. The labeling is associated with a semantic scope of intent considered by the clients. A combination of propagation operations and learning algorithms using the selected set of labeled conversational logs are applied to a remaining corpus of the plurality of conversational logs to train the automated response system according to the semantic scope of intent.Type: GrantFiled: August 31, 2018Date of Patent: November 10, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam Ho, Robert L. Yates, Blake McGregor, Rajendra G. Ugrani, Neil R. Mallinar, Abhishek Shah, Ayush Gupta
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Publication number: 20200074984Abstract: Embodiments for training an automated response system using weak supervision and co-training in a computing environment are provided. A plurality of conversational logs comprising interactive dialog sessions between agents and clients for a given product or service are received. A subset of the plurality of conversational logs are retrieved according to a defined criterion, and a selected set of the subset of the plurality of retrieved conversational logs are labeled by a user. The labeling is associated with a semantic scope of intent considered by the clients. A combination of propagation operations and learning algorithms using the selected set of labeled conversational logs are applied to a remaining corpus of the plurality of conversational logs to train the automated response system according to the semantic scope of intent.Type: ApplicationFiled: August 31, 2018Publication date: March 5, 2020Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Tin Kam HO, Robert L. YATES, Blake MCGREGOR, Rajendra G. UGRANI, Neil R. MALLINAR, Abhishek SHAH, Ayush GUPTA