Patents by Inventor Kelly Huffman

Kelly Huffman 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).

  • INCREASING SOCIAL MEDIA PRESENCE USING MACHINE-LEARNING RELEVANCE TECHNIQUES
    Publication number: 20220198509
    Abstract: According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.
    Type: Application
    Filed: March 9, 2022
    Publication date: June 23, 2022
    Inventors: Wook Jin Chung, Kiryl Lashuk, Kelly Huffman
  • Increasing social media presence using machine-learning relevance techniques
    Patent number: 11276075
    Abstract: According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.
    Type: Grant
    Filed: April 2, 2020
    Date of Patent: March 15, 2022
    Assignee: Twitter, Inc.
    Inventors: Wook Jin Chung, Kiryl Lashuk, Kelly Huffman
  • Increasing social media presence using machine-learning relevance techniques
    Patent number: 10748172
    Abstract: According to an implementation, a system includes a social media messaging platform configured to exchange messages, over a network, among a plurality of computing devices. The exchange of messages is based on a connection graph stored on the messaging platform. The social media messaging platform includes a registration manager configured to register an account for an entity to boost a social media presence of the entity on the social media messaging platform, and a social media presence booster having a machine-learning relevance engine configured to programmatically match the entity's content with relevant entities. The social media presence booster is configured to automatically and programmatically boost the entity's content to the relevant entities, and increase, over time, a number of connections in the connection graph between the account and other accounts on the social media messaging platform in response to the boosted content.
    Type: Grant
    Filed: March 3, 2017
    Date of Patent: August 18, 2020
    Assignee: Twitter, Inc.
    Inventors: Wook Jin Chung, Kiryl Lashuk, Kelly Huffman
  • INCREASING SOCIAL MEDIA PRESENCE USING MACHINE-LEARNING RELEVANCE TECHNIQUES
    Publication number: 20200234330
    Abstract: According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.
    Type: Application
    Filed: April 2, 2020
    Publication date: July 23, 2020
    Inventors: Wook Jin Chung, Kiryl Lashuk, Kelly Huffman
  • INCREASING SOCIAL MEDIA PRESENCE USING MACHINE-LEARNING RELEVANCE TECHNIQUES
    Publication number: 20180253753
    Abstract: According to an implementation, a system includes a social media messaging platform configured to exchange messages, over a network, among a plurality of computing devices. The exchange of messages is based on a connection graph stored on the messaging platform. The social media messaging platform includes a registration manager configured to register an account for an entity to boost a social media presence of the entity on the social media messaging platform, and a social media presence booster having a machine-learning relevance engine configured to programmatically match the entity's content with relevant entities. The social media presence booster is configured to automatically and programmatically boost the entity's content to the relevant entities, and increase, over time, a number of connections in the connection graph between the account and other accounts on the social media messaging platform in response to the boosted content.
    Type: Application
    Filed: March 3, 2017
    Publication date: September 6, 2018
    Inventors: Wook Jin Chung, Kiryl Lashuk, Kelly Huffman