Patents by Inventor Maryam Samim

Maryam Samim 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).

  • Predictive resolutions for tickets using semi-supervised machine learning
    Patent number: 11556843
    Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system collects information associated with trouble tickets each including a problem abstract and a log text. The method includes analyzing the log text to obtain a problem resolution for that ticket; defining ticket clusters according to the problem abstracts, and labeling the clusters. The processing system creates a library of the labeled clusters, each entry including a cluster label, a problem abstract for that cluster, and a resolution summary for that problem abstract, indicating a mapping of the problem abstract to the resolution summary for that cluster. The method includes training, based on the mapping, machine-learning applications for a predicted resolution summary for each cluster and for classifying a new ticket. The method includes assigning the new ticket to a cluster according to the classifying. Other embodiments are disclosed.
    Type: Grant
    Filed: July 15, 2019
    Date of Patent: January 17, 2023
    Assignee: AT&T Intellectual Property I, L.P.
    Inventors: Elissa Backas, Yang Qu, Hassan Chughtai, Maryam Samim, Nelson Cuebas, Roque Rios, III, Craig Scantlin, Donghoon Shin, Heesook Choi
  • Predictive Resolutions for Tickets Using Semi-Supervised Machine Learning
    Publication number: 20210019648
    Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system collects information associated with trouble tickets each including a problem abstract and a log text. The method includes analyzing the log text to obtain a problem resolution for that ticket; defining ticket clusters according to the problem abstracts, and labeling the clusters. The processing system creates a library of the labeled clusters, each entry including a cluster label, a problem abstract for that cluster, and a resolution summary for that problem abstract, indicating a mapping of the problem abstract to the resolution summary for that cluster. The method includes training, based on the mapping, machine-learning applications for a predicted resolution summary for each cluster and for classifying a new ticket. The method includes assigning the new ticket to a cluster according to the classifying. Other embodiments are disclosed.
    Type: Application
    Filed: July 15, 2019
    Publication date: January 21, 2021
    Applicant: AT&T Intellectual Property I, L.P.
    Inventors: Elissa Backas, Yang Qu, Hassan Chughtai, Maryam Samim, Nelson Cuebas, Roque Rios, III, Craig Scantlin, Donghoon Shin, Heesook Choi