Patents by Inventor Michael Dekshenieks

Michael Dekshenieks 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: 11010696
    Abstract: Examples of job allocation are described hereon. In an example, a job for allocation may be received. The job may be analyzed to obtain information pertaining to the job. The information may comprise at least one of a domain of the job and a priority level of the job. Further, performance of resources may be determined to provide resource information. The resource information may be determined using a supervised learning model comprising a job vector for each job type and a resource vector corresponding to each resource. The resource information may include a list of resources with at least one of a corresponding probability of each resource completing the job and a performance score of each resource. Based on the job information and the resource information, the resource may be recommended for the job using an expertise-estimation modeling technique and the job may be assigned to the recommended resource, accordingly.
    Type: Grant
    Filed: March 9, 2018
    Date of Patent: May 18, 2021
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Guanglei Xiong, Chung-Sheng Li, Christopher Cole, Michael Dekshenieks, Kayhan Moharreri
  • Publication number: 20180260746
    Abstract: Examples of job allocation are described hereon. In an example, a job for allocation may be received. The job may be analyzed to obtain information pertaining to the job. The information may comprise at least one of a domain of the job and a priority level of the job. Further, performance of resources may be determined to provide resource information. The resource information may be determined using a supervised learning model comprising a job vector for each job type and a resource vector corresponding to each resource. The resource information may include a list of resources with at least one of a corresponding probability of each resource completing the job and a performance score of each resource. Based on the job information and the resource information, the resource may be recommended for the job using an expertise-estimation modeling technique and the job may be assigned to the recommended resource, accordingly.
    Type: Application
    Filed: March 9, 2018
    Publication date: September 13, 2018
    Inventors: Guanglei Xiong, Chung-Sheng Li, Christopher Cole, Michael Dekshenieks, Kayhan Moharreri