Patents by Inventor Srinivasa Phani Kumar Gadde

Srinivasa Phani Kumar Gadde 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).

  • Patent number: 12001775
    Abstract: A data corpus is partitioned into text strings for header classification. A group characteristic is computed for a text string, and whether the group characteristic satisfies a group characteristic criterion is determined. The text string may be disqualified from header classification if the group characteristic criterion is not satisfied, or one or more font characteristics may be determined for the text string if the group characteristic criterion is satisfied. A font characteristic that meets one or more prevalence criteria may be identified and evaluated to determine whether the font characteristic meets at least one font characteristic criterion. The text string may be disqualified from header classification if the font characteristic criterion is not satisfied, or if the font characteristic meets the font characteristic criterion, the text string is classified as a header, and tagged content is generated by applying a header tag to the text string.
    Type: Grant
    Filed: June 13, 2023
    Date of Patent: June 4, 2024
    Assignee: Oracle International Corporation
    Inventors: Sagar Gollamudi, Vishank Bhatia, Xu Zhong, Thanh Long Duong, Mark Johnson, Srinivasa Phani Kumar Gadde, Vishal Vishnoi
  • Publication number: 20240169153
    Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.
    Type: Application
    Filed: January 31, 2024
    Publication date: May 23, 2024
    Applicant: Oracle International Corporation
    Inventors: Crystal C. Pan, Guatam Singaraju, Vishal Vishnoi, Srinivasa Phani Kumar Gadde
  • Publication number: 20240169155
    Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.
    Type: Application
    Filed: January 26, 2024
    Publication date: May 23, 2024
    Applicant: Oracle International Corporation
    Inventors: Vishal Vishnoi, Xin Xu, Elias Luqman Jalaluddin, Srinivasa Phani Kumar Gadde, Crystal C. Pan, Mark Edward Johnson, Thanh Long Duong, Balakota Srinivas Vinnakota, Manish Parekh
  • Patent number: 11989523
    Abstract: The present disclosure relates to chatbot systems, and more particularly, to techniques for obtaining data items for input to a chatbot. In certain embodiments, a chatbot system includes a component that can be invoked by a chatbot in the chatbot system to obtain data items needed by the chatbot. The component can be invoked based on a reference to the component in a dialog flow definition configured for the chatbot. The reference to the component can indicate a composite entity that the component will use to determine how the data items are obtained from a user. The composite entity acts as a container for the data items and may be configured separately from the dialog flow definition of the chatbot. The data items can be obtained based on rules specified in a composite entity definition configured for the composite entity.
    Type: Grant
    Filed: February 23, 2023
    Date of Patent: May 21, 2024
    Assignee: Oracle Inernational Corporation
    Inventors: Srinivasa Phani Kumar Gadde, Manish Parekh, Steven Martijn Davelaar, Manmohit Rekhi
  • Publication number: 20240126795
    Abstract: Techniques are disclosed herein for integrating document question answering in an artificial intelligence-based platform, such as a chatbot system. The techniques include receiving a query from a user, rewriting the query to include one or more specific descriptors, computing an embedding vector for the rewritten query, retrieving one or more textual passages from a document store utilizing the embedding vector for the rewritten query, determining one or more answers to the rewritten query within the one or more textual passages, and returning the one or more answers.
    Type: Application
    Filed: October 13, 2023
    Publication date: April 18, 2024
    Applicant: Oracle International Corporation
    Inventors: Xu Zhong, Thanh Long Duong, Mark Edward Johnson, Charles Woodrow Dickstein, King-Hwa Lee, Xin Xu, Srinivasa Phani Kumar Gadde, Vishal Vishnoi, Christopher Kennewick, Balakota Srinivas Vinnakota, Raefer Christopher Gabriel
  • Publication number: 20240126800
    Abstract: Techniques for maintaining list-type text formatting when converting content from a source content format to a destination content format are disclosed. A system generates text content by applying text formatting tags to segments of characters obtained from a source electronic document. The system parses a static-display type source electronic document to obtain character data of the characters in the source document. The system analyzes the parsed data to identify text arranged in a list-type text format in the source document. The system generates text content in a destination content format different from the source format by applying tags to segments of the text content designating the segments items in a list.
    Type: Application
    Filed: May 31, 2023
    Publication date: April 18, 2024
    Applicant: Oracle International Corporation
    Inventors: Vishank Bhatia, Xu Zhong, Thanh Long Duong, Mark Johnson, Srinivasa Phani Kumar Gadde, Vishal Vishnoi
  • Publication number: 20240095584
    Abstract: Techniques are disclosed herein for objective function optimization in target based hyperparameter tuning. In one aspect, a computer-implemented method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that comprises a domain score for each domain that is calculated based on a number of instances within an evaluation dataset that are correctly or incorrectly predicted by the machine learning algorithm during a given trial. For each trial of a hyperparameter tuning process: training the machine learning algorithm to generate a machine learning model, running the machine learning model in different domains using the set of hyperparameter values, evaluating the machine learning model for each domain, and once the machine learning model has reached convergence, outputting at least one machine learning model.
    Type: Application
    Filed: May 15, 2023
    Publication date: March 21, 2024
    Applicant: Oracle International Corporation
    Inventors: Ying Xu, Vladislav Blinov, Ahmed Ataallah Ataallah Abobakr, Thanh Long Duong, Mark Edward Johnson, Elias Luqman Jalaluddin, Xin Xu, Srinivasa Phani Kumar Gadde, Vishal Vishnoi, Poorya Zaremoodi, Umanga Bista
  • Publication number: 20240095454
    Abstract: Techniques are provided for using context tags in named-entity recognition (NER) models. In one particular aspect, a method is provided that includes receiving an utterance, generating embeddings for words of the utterance, generating a regular expression and gazetteer feature vector for the utterance, generating a context tag distribution feature vector for the utterance, concatenating or interpolating the embeddings with the regular expression and gazetteer feature vector and the context tag distribution feature vector to generate a set of feature vectors, generating an encoded form of the utterance based on the set of feature vectors, generating log-probabilities based on the encoded form of the utterance, and identifying one or more constraints for the utterance.
    Type: Application
    Filed: November 28, 2023
    Publication date: March 21, 2024
    Applicant: Oracle International Corporation
    Inventors: Duy Vu, Tuyen Quang Pham, Cong Duy Vu Hoang, Srinivasa Phani Kumar Gadde, Thanh Long Duong, Mark Edward Johnson, Vishal Vishnoi
  • Publication number: 20240086767
    Abstract: Techniques are disclosed herein for continuous hyperparameter tuning with automatic domain weight adjustment based on periodic performance checkpoints. In one aspect, a method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that is defined at least in part on a plurality of domains of a search space that is associated with the machine learning algorithm. For each trial of a hyperparameter tuning process: running the machine learning algorithm in different domains using the set of hyperparameter values, periodically checking a performance of the machine learning algorithm in the different domains based on the hyperparameter objective function; and continuing hyperparameter tuning with a new set of hyperparameter values after automatically adjusting the domain weights according to a regression status of the different domains.
    Type: Application
    Filed: April 3, 2023
    Publication date: March 14, 2024
    Applicant: Oracle International Corporation
    Inventors: Ying Xu, Vladislav Blinov, Ahmed Ataallah Ataallah Abobakr, Mark Edward Johnson, Thanh Long Duong, Srinivasa Phani Kumar Gadde, Vishal Vishnoi, Xin Xu, Elias Luqman Jalaluddin, Umanga Bista
  • Patent number: 11928430
    Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.
    Type: Grant
    Filed: September 10, 2020
    Date of Patent: March 12, 2024
    Assignee: Oracle International Corporation
    Inventors: Crystal C. Pan, Gautam Singaraju, Vishal Vishnoi, Srinivasa Phani Kumar Gadde
  • Patent number: 11922123
    Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.
    Type: Grant
    Filed: September 30, 2021
    Date of Patent: March 5, 2024
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Vishal Vishnoi, Xin Xu, Elias Luqman Jalaluddin, Srinivasa Phani Kumar Gadde, Crystal C. Pan, Mark Edward Johnson, Thanh Long Duong, Balakota Srinivas Vinnakota, Manish Parekh
  • Patent number: 11914943
    Abstract: Techniques for generating text content arranged in a consistent read order from a source document including text corresponding to different read orders are disclosed. A system parses a binary file representing an electronic document to identify characters and metadata associated with the characters. The system pre-sorts a character order of characters in each line of the electronic document to generate an ordered list of characters arranged according to the right-to-left reading order. The system performs a layout-mirroring operation to change a position of characters within the modified document relative to a right edge of the document and a left edge of the document. Subsequent to performing layout-mirroring, the system identifies native left-to-right reading-order text in-line with the native right-to-left reading-order text.
    Type: Grant
    Filed: February 15, 2023
    Date of Patent: February 27, 2024
    Assignee: Oracle International Corporation
    Inventors: Xu Zhong, Vishank Bhatia, Thanh Long Duong, Mark Johnson, Srinivasa Phani Kumar Gadde, Vishal Vishnoi
  • Publication number: 20240061832
    Abstract: Techniques are disclosed herein for converting a natural language utterance to an intermediate database query representation. An input string is generated by concatenating a natural language utterance with a database schema representation for a database. Based on the input string, a first encoder generates one or more embeddings of the natural language utterance and the database schema representation. A second encoder encodes relations between elements in the database schema representation and words in the natural language utterance based on the one or more embeddings. A grammar-based decoder generates an intermediate database query representation based on the encoded relations and the one or more embeddings. Based on the intermediate database query representation and an interface specification, a database query is generated in a database query language.
    Type: Application
    Filed: June 14, 2023
    Publication date: February 22, 2024
    Applicant: Oracle International Corporation
    Inventors: Cong Duy Vu Hoang, Stephen Andrew McRitchie, Mark Edward Johnson, Shivashankar Subramanian, Aashna Devang Kanuga, Nitika Mathur, Gioacchino Tangari, Steve Wai-Chun Siu, Poorya Zaremoodi, Vasisht Raghavendra, Thanh Long Duong, Srinivasa Phani Kumar Gadde, Vishal Vishnoi, Christopher Mark Broadbent, Philip Arthur, Syed Najam Abbas Zaidi
  • Publication number: 20240062011
    Abstract: Techniques are disclosed herein for using named entity recognition to resolve entity expression while transforming natural language to a meaning representation language. In one aspect, a method includes accessing natural language text, predicting, by a first machine learning model, a class label for a token in the natural language text, predicting, by a second machine-learning model, operators for a meaning representation language and a value or value span for each attribute of the operators, in response to determining that the value or value span for a particular attribute matches the class label, converting a portion of the natural language text for the value or value span into a resolved format, and outputting syntax for the meaning representation language. The syntax comprises the operators with the portion of the natural language text for the value or value span in the resolved format.
    Type: Application
    Filed: July 13, 2023
    Publication date: February 22, 2024
    Applicant: Oracle International Corporation
    Inventors: Aashna Devang Kanuga, Cong Duy Vu Hoang, Mark Edward Johnson, Vasisht Raghavendra, Yuanxu Wu, Steve Wai-Chun Siu, Nitika Mathur, Gioacchino Tangari, Shubham Pawankumar Shah, Vanshika Sridharan, Zikai Li, Diego Andres Cornejo Barra, Stephen Andrew McRitchie, Christopher Mark Broadbent, Vishal Vishnoi, Srinivasa Phani Kumar Gadde, Poorya Zaremoodi, Thanh Long Duong, Bhagya Gayathri Hettige, Tuyen Quang Pham, Arash Shamaei, Thanh Tien Vu, Yakupitiyage Don Thanuja Samodhve Dharmasiri
  • Publication number: 20240061992
    Abstract: Techniques for generating formatting tags for textual content obtained from a source electronic document are disclosed. A system parses a digital file to obtain information about characters in an electronic document. The system applies tags to text generated based on the textual content of the electronic document by creating segments of textually-consecutive characters and applying corresponding text formatting style tags to the segments. The system further identifies segments of text overlapping bounding boxes in the electronic document. The system generates textual content including a segment of text and a corresponding hyperlink associated with the segment of text. The system further generates textual content by selectively applying line breaks from the source electronic document in the textual content.
    Type: Application
    Filed: January 6, 2023
    Publication date: February 22, 2024
    Applicant: Oracle International Corporation
    Inventors: Vishank Bhatia, Xu Zhong, Thanh Long Duong, Mark Johnson, Srinivasa Phani Kumar Gadde, Vishal Vishnoi, King-Hwa Lee, Christopher Kennewick
  • Publication number: 20240061989
    Abstract: Techniques for generating text content arranged in a consistent read order from a source document including text corresponding to different read orders are disclosed. A system parses a binary file representing an electronic document to identify characters and metadata associated with the characters. The system pre-sorts a character order of characters in each line of the electronic document to generate an ordered list of characters arranged according to the right-to-left reading order. The system performs a layout-mirroring operation to change a position of characters within the modified document relative to a right edge of the document and a left edge of the document. Subsequent to performing layout-mirroring, the system identifies native left-to-right reading-order text in-line with the native right-to-left reading-order text.
    Type: Application
    Filed: February 15, 2023
    Publication date: February 22, 2024
    Applicant: Oracle International Corporation
    Inventors: Xu Zhong, Vishank Bhatia, Thanh Long Duong, Mark Johnson, Srinivasa Phani Kumar Gadde, Vishal Vishnoi
  • Publication number: 20240013780
    Abstract: Techniques for data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes generating a list of values to cover for an entity, selecting utterances from a set of data that have context for the entity, converting the utterances into templates, where each template of the templates comprises a slot that maps to the list of values for the entity, selecting a template from the templates, selecting a value from the list of values based on the mapping between the slot within the selected template and the list of values for the entity; and creating an artificial utterance based on the selected template and the selected value, where the creating the artificial utterance comprises inserting the selected value into the slot of the selected template that maps to the list of values for the entity.
    Type: Application
    Filed: September 21, 2023
    Publication date: January 11, 2024
    Applicant: Oracle International Corporation
    Inventors: Srinivasa Phani Kumar Gadde, Yuanxu Wu, Aashna Devang Kanuga, Elias Luqman Jalaluddin, Vishal Vishnoi, Mark Edward Johnson
  • Patent number: 11868727
    Abstract: Techniques are provided for using context tags in named-entity recognition (NER) models. In one particular aspect, a method is provided that includes receiving an utterance, generating embeddings for words of the utterance, generating a regular expression and gazetteer feature vector for the utterance, generating a context tag distribution feature vector for the utterance, concatenating or interpolating the embeddings with the regular expression and gazetteer feature vector and the context tag distribution feature vector to generate a set of feature vectors, generating an encoded form of the utterance based on the set of feature vectors, generating log-probabilities based on the encoded form of the utterance, and identifying one or more constraints for the utterance.
    Type: Grant
    Filed: January 19, 2022
    Date of Patent: January 9, 2024
    Assignee: Oracle International Corporation
    Inventors: Duy Vu, Tuyen Quang Pham, Cong Duy Vu Hoang, Srinivasa Phani Kumar Gadde, Thanh Long Duong, Mark Edward Johnson, Vishal Vishnoi
  • Publication number: 20230419040
    Abstract: Novel techniques are described for data augmentation using a two-stage entity-aware augmentation to improve model robustness to entity value changes for intent prediction.
    Type: Application
    Filed: February 1, 2023
    Publication date: December 28, 2023
    Applicant: Oracle International Corporation
    Inventors: Ahmed Ataallah Ataallah Abobakr, Shivashankar Subramanian, Ying Xu, Vladislav Blinov, Umanga Bista, Tuyen Quang Pham, Thanh Long Duong, Mark Edward Johnson, Elias Luqman Jalaluddin, Vanshika Sridharan, Xin Xu, Srinivasa Phani Kumar Gadde, Vishal Vishnoi
  • Publication number: 20230419127
    Abstract: Novel techniques are described for negative entity-aware augmentation using a two-stage augmentation to improve the stability of the model to entity value changes for intent prediction. In some embodiments, a method comprises accessing a first set of training data for an intent prediction model, the first set of training data comprising utterances and intent labels; applying one or more negative entity-aware data augmentation techniques to the first set of training data, depending on the tuning requirements for hyper-parameters, to result in a second set of training data, where the one or more negative entity-aware data augmentation techniques comprise Keyword Augmentation Technique (“KAT”) plus entity without context technique and KAT plus entity in random context as OOD technique; combining the first set of training data and the second set of training data to generate expanded training data; and training the intent prediction model using the expanded training data.
    Type: Application
    Filed: February 1, 2023
    Publication date: December 28, 2023
    Applicant: Oracle International Corporation
    Inventors: Ahmed Ataallah Ataallah Abobakr, Shivashankar Subramanian, Ying Xu, Vladislav Blinov, Umanga Bista, Tuyen Quang Pham, Thanh Long Duong, Mark Edward Johnson, Elias Luqman Jalaluddin, Vanshika Sridharan, Xin Xu, Srinivasa Phani Kumar Gadde, Vishal Vishnoi