Patents by Inventor RAKSHA JALAN

RAKSHA JALAN 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: 12206945
    Abstract: An electronic device for generation of recommendations using trust-based embeddings is provided. The electronic device determines first correlation information of a first set of users associated with a first domain. The electronic device generates, based on the first correlation information, a first vector indicating a trust embedding of a first user with respect to the first set of users, in the first domain. The electronic device receives second correlation information associated with a second set of users associated with a second domain. The electronic device utilizes a Graph Attention Network model for the second correlation information to generate a second vector indicative of a trust embedding of the first user, with respect to the second set of users, in the second domain. The electronic device applies a recommendation model on the first vector and the second vector to recommend one or more items to the first user.
    Type: Grant
    Filed: March 21, 2023
    Date of Patent: January 21, 2025
    Assignee: SONY GROUP CORPORATION
    Inventors: Raksha Jalan, Prosenjit Biswas, Brijraj Singh
  • Publication number: 20240331008
    Abstract: Provided is an electronic device for social network information-based recommendation using transformer model. The electronic device receives first history information associated with a set of users for an item of a set of items and determines first similarity information associated with each user with respect to remaining users of the set of users. Further, the electronic device receives social network information associated each user with respect to remaining users of the set of users. The electronic device determines first embedding associated with each user for the item, based on the first history information, the first similarity information, and the social network information. A first transformer model is applied on the first embedding to determine at least user from set of users for the item. First recommendation information including the determined at least one users for the item is rendered.
    Type: Application
    Filed: March 7, 2024
    Publication date: October 3, 2024
    Inventors: RAKSHA JALAN, TUSHAR PRAKASH, NAOYUKI ONOE
  • Publication number: 20230385607
    Abstract: An electronic device and a method for implementation of hypergraph-based collaborative filtering recommendations. The electronic device receives a collaborative filtering graph corresponding to a set of users and a set of items. The electronic device determines a first set of user embeddings and a first set of item embeddings. The electronic device applies a semantic clustering model to determine a second set of user embeddings and a second set of item embeddings. The electronic device constructs a hypergraph to determine a third set of user embeddings and a third set of item embeddings. The electronic device determines a first contrastive loss and a second contrastive loss to determine a collaborative filtering score. The electronic device determines a recommendation of an item for a user based on the determined collaborative filtering score. The electronic device renders the determined recommended item on a display device.
    Type: Application
    Filed: May 17, 2023
    Publication date: November 30, 2023
    Inventors: PROSENJIT BISWAS, BRIJRAJ SINGH, RAKSHA JALAN
  • Publication number: 20230319358
    Abstract: An electronic device for generation of recommendations using trust-based embeddings is provided. The electronic device determines first correlation information of a first set of users associated with a first domain. The electronic device generates, based on the first correlation information, a first vector indicating a trust embedding of a first user with respect to the first set of users, in the first domain. The electronic device receives second correlation information associated with a second set of users associated with a second domain. The electronic device utilizes a Graph Attention Network model for the second correlation information to generate a second vector indicative of a trust embedding of the first user, with respect to the second set of users, in the second domain. The electronic device applies a recommendation model on the first vector and the second vector to recommend one or more items to the first user.
    Type: Application
    Filed: March 21, 2023
    Publication date: October 5, 2023
    Inventors: RAKSHA JALAN, PROSENJIT BISWAS, BRIJRAJ SINGH
  • Publication number: 20230316086
    Abstract: An electronic device and a method for implementation for machine learning model update based on dataset or feature unlearning are disclosed. The electronic device receives a data subset of a first dataset associated with a user. A first machine learning model is trained based on the first dataset. The electronic device trains a second machine learning model based on the received data subset. The electronic device applies a transformation function on the trained first machine learning model based on the trained second machine learning model. The electronic device updates the trained first machine learning model, based on the application of the transformation function. The update of the trained first machine learning model corresponds to an unlearning of at least one of the received data subset or a set of features associated with the second machine learning model.
    Type: Application
    Filed: January 26, 2023
    Publication date: October 5, 2023
    Inventors: BRIJRAJ SINGH, RAKSHA JALAN, PROSENJIT BISWAS