Patents by Inventor Rajat Mahajan

Rajat Mahajan 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).

  • Techniques for linking data to provide improved searching capabilities
    Patent number: 11797549
    Abstract: A machine-learning model may be previously trained with a supervised learning algorithm to identify whether a pair of labels provided as input are similar. A locality sensitive hashing forest (LSH) may be generated for the set of candidate labels. When a user later identifies an input label (e.g., by search query, by interface selection, etc.) the input label may be used to query the LSH forest to identify a subset of the candidate labels. This subset may be used to generate respective pairs comprising the input label, one of the subset candidate labels, and a corresponding feature set generated for the pair. This data may be provided to the model to identify a degree to which the pair of labels are similar. The user may be provided one or more recommendations including similar terms identified from the model's output.
    Type: Grant
    Filed: November 15, 2022
    Date of Patent: October 24, 2023
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Gopal Srinivasa Raghavan, Abhiram Madhukar Gujjewar, Ganesh Seetharaman, Jai Motwani, Sayon Dutta, Rajat Mahajan, Manasjyoti Sharma
  • TECHNIQUES FOR LINKING DATA TO PROVIDE IMPROVED SEARCHING CAPABILITIES
    Publication number: 20230076308
    Abstract: A machine-learning model may be previously trained with a supervised learning algorithm to identify whether a pair of labels provided as input are similar. A locality sensitive hashing forest (LSH) may be generated for the set of candidate labels. When a user later identifies an input label (e.g., by search query, by interface selection, etc.) the input label may be used to query the LSH forest to identify a subset of the candidate labels. This subset may be used to generate respective pairs comprising the input label, one of the subset candidate labels, and a corresponding feature set generated for the pair. This data may be provided to the model to identify a degree to which the pair of labels are similar. The user may be provided one or more recommendations including similar terms identified from the model's output.
    Type: Application
    Filed: November 15, 2022
    Publication date: March 9, 2023
    Applicant: Oracle International Corporation
    Inventors: Gopal Srinivasa Raghavan, Abhiram Madhukar Gujjewar, Ganesh Seetharaman, Jai Motwani, Sayon Dutta, Rajat Mahajan, Manasjyoti Sharma
  • Techniques for linking data to provide improved searching capabilities
    Patent number: 11531675
    Abstract: A machine-learning model may be previously trained with a supervised learning algorithm to identify whether a pair of labels provided as input are similar. A locality sensitive hashing forest (LSH) may be generated for the set of candidate labels. When a user later identifies an input label (e.g., by search query, by interface selection, etc.) the input label may be used to query the LSH forest to identify a subset of the candidate labels. This subset may be used to generate respective pairs comprising the input label, one of the subset candidate labels, and a corresponding feature set generated for the pair. This data may be provided to the model to identify a degree to which the pair of labels are similar. The user may be provided one or more recommendations including similar terms identified from the model's output.
    Type: Grant
    Filed: July 19, 2021
    Date of Patent: December 20, 2022
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Gopal Srinivasa Raghavan, Abhiram Madhukar Gujjewar, Ganesh Seetharaman, Jai Motwani, Sayon Dutta, Rajat Mahajan, Manasjyoti Sharma