Patents Assigned to SEEKR TECHNOLOGIES, INC.
  • Patent number: 11921731
    Abstract: One or more techniques and/or systems are provided for implementing a pipeline used to generate, train, test, and implement a document scoring model for assigning document scores to documents. Features from various sources are combined to create a joined page level feature set, a joined domain level feature set, and a host level feature set. Numerical features and content features are extracted from ground truth documents and random documents. The numerical features are joined with the joined feature sets to create a set of joined features. The document scoring model is trained using the set of joined features and a training technique. A document is scored with a document score using the document scoring model based upon the content features and the set of joined features with document scores obtained during training.
    Type: Grant
    Filed: September 2, 2022
    Date of Patent: March 5, 2024
    Assignee: SEEKR TECHNOLOGIES, INC.
    Inventors: Ricardo Baeza-Yates, Berkant Barla Cambazoglu, Darshan Mallenahalli Shankaralingappa, Matteo Catena
  • Patent number: 11893981
    Abstract: A scoring system and method identifies personal attacks in a piece of audio content and generates a civility score for the piece of audio content that can differentiate between personal attacks and vernacular/casual banter. The piece of audio content may be a podcast.
    Type: Grant
    Filed: September 7, 2023
    Date of Patent: February 6, 2024
    Assignee: SEEKR TECHNOLOGIES INC.
    Inventors: Robin J. Clark, Ali Taleb Zadeh Kasgari, Stefanos Poulis
  • Publication number: 20230185814
    Abstract: One or more techniques and/or systems are provided for implementing a pipeline used to generate, train, test, and implement a document scoring model for assigning document scores to documents. Features from various sources are combined to create a joined page level feature set, a joined domain level feature set, and a host level feature set. Numerical features and content features are extracted from ground truth documents and random documents. The numerical features are joined with the joined feature sets to create a set of joined features. The document scoring model is trained using the set of joined features and a training technique. A document is scored with a document score using the document scoring model based upon the content features and the set of joined features with document scores obtained during training.
    Type: Application
    Filed: September 2, 2022
    Publication date: June 15, 2023
    Applicant: SEEKR TECHNOLOGIES, INC.
    Inventors: Ricardo Baeza-Yates, Berkant Barla Cambazoglu, Darshan Mallenahalli Shankaralingappa, Matteo Catena