Patents by Inventor Colleen Lhota

Colleen Lhota 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: 11188855
    Abstract: A method and system for improving a machine learning task assignment process is provided to address productivity with respect to satisfaction. The method includes connecting hardware devices to a server system. Job related data associated with job roles for individuals is retrieved and associated with a time period. Work related items of the job related data are presented and selections for work related items are retrieved via selectors for the work items. Expected and actual satisfaction ratings for the work related items are received and analyzed in accordance with an order in which they are received. At least one work item is assigned to a user and a specialized memory repository is generated within a portion of a memory device. Results of the assignment are stored within the specialized memory repository. Self-learning software code for executing future task assignment processes is generated and modified based on reported satisfaction ratings.
    Type: Grant
    Filed: March 26, 2018
    Date of Patent: November 30, 2021
    Assignee: International Business Machines Corporation
    Inventors: Colleen Lhota, Ashley K. Silva, Aksel Davis, Jocelyn Sese
  • Patent number: 11151119
    Abstract: Systems and methods for assessing the veracity of content are described. The method may include determining a truth rating for each of a plurality of factual claims in a document, generating a veracity score for the document based on the truth rating for each of the identified plurality of factual claims, generating a meta-data score for the document based on metadata of the document, and generating a content structure score for the document. The method may then include generating a reliability index for the document based on the veracity score and the meta-data score and presenting the scores and the overall reliability index to a user via a user application.
    Type: Grant
    Filed: November 30, 2018
    Date of Patent: October 19, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Randy A. Rendahl, Glenn Fuller, Colleen Lhota
  • Publication number: 20200174991
    Abstract: Systems and methods for assessing the veracity of content are described. The method may include determining a truth rating for each of a plurality of factual claims in a document, generating a veracity score for the document based on the truth rating for each of the identified plurality of factual claims, generating a meta-data score for the document based on metadata of the document, and generating a content structure score for the document. The method may then include generating a reliability index for the document based on the veracity score and the meta-data score and presenting the scores and the overall reliability index to a user via a user application.
    Type: Application
    Filed: November 30, 2018
    Publication date: June 4, 2020
    Inventors: Randy A. Rendahl, Glenn Fuller, Colleen Lhota
  • Publication number: 20190295013
    Abstract: A method and system for improving a machine learning task assignment process is provided to address productivity with respect to satisfaction. The method includes connecting hardware devices to a server system. Job related data associated with job roles for individuals is retrieved and associated with a time period. Work related items of the job related data are presented and selections for work related items are retrieved via selectors for the work items. Expected and actual satisfaction ratings for the work related items are received and analyzed in accordance with an order in which they are received. At least one work item is assigned to a user and a specialized memory repository is generated within a portion of a memory device. Results of the assignment are stored within the specialized memory repository. Self-learning software code for executing future task assignment processes is generated and modified based on reported satisfaction ratings.
    Type: Application
    Filed: March 26, 2018
    Publication date: September 26, 2019
    Inventors: Colleen Lhota, Ashley K. Silva, Aksel Davis, Jocelyn Sese