Patents by Inventor Jacob Alexander Mannix

Jacob Alexander Mannix 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: 11475018
    Abstract: Methods, systems, and devices supporting determining user and data record relationships based on vector space embeddings are described. Some database systems may receive data record access indications corresponding to data records accessed by users. A database system may generate, based on the data record access indications, user sessions for the users, data record sessions for the data records, or a combination for users and data records. For example, a user session may correspond to a respective user and include a record identifier associated with each data record accessed by the user. The system may generate, in a vector space, vectors from the sessions using an embedding operation, where each vector corresponds to a respective user or data record. The system may determine relationships between the users, data records, or both based on the vectors and may transmit an indication of at least one data record based on the relationships.
    Type: Grant
    Filed: January 22, 2020
    Date of Patent: October 18, 2022
    Assignee: salesforce.com, inc.
    Inventors: Guillaume Kempf, Jacob Alexander Mannix, Arvind Srikantan
  • Publication number: 20220229843
    Abstract: Methods, computer readable media, and devices for modeling heterogeneous feature sets for use in personalized search are provided. The method may include generating a similarity factor for each of a plurality of personalization features. For each of the plurality of personalization features, a personalization feature weight is calculated. Each personalization feature weight is converted into a probability distribution and each similarity factor is scaled based on a corresponding probability distribution. Based on each scaled similarity factor, a most recently used affinity value is generated for each corresponding personalization feature. The most recently used affinity values are used to generate a ranking function for use as part of personalized search.
    Type: Application
    Filed: January 21, 2021
    Publication date: July 21, 2022
    Inventors: Ashish Bharadwaj Srinivasa, Jacob Alexander Mannix, Mario Sergio Rodriguez
  • Publication number: 20210224284
    Abstract: Methods, systems, and devices supporting determining user and data record relationships based on vector space embeddings are described. Some database systems may receive data record access indications corresponding to data records accessed by users. A database system may generate, based on the data record access indications, user sessions for the users, data record sessions for the data records, or a combination for users and data records. For example, a user session may correspond to a respective user and include a record identifier associated with each data record accessed by the user. The system may generate, in a vector space, vectors from the sessions using an embedding operation, where each vector corresponds to a respective user or data record. The system may determine relationships between the users, data records, or both based on the vectors and may transmit an indication of at least one data record based on the relationships.
    Type: Application
    Filed: January 22, 2020
    Publication date: July 22, 2021
    Inventors: Guillaume Kempf, Jacob Alexander Mannix, Arvind Srikantan