Patents by Inventor Michael Itkin

Michael Itkin 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: 12118294
    Abstract: Systems, methods, and products for auto tagging structured PDF documents that do not have accessibility tags. In one embodiment, structured PDF documents having accessibility tags are first parsed and analyzed to organize the visual components of the documents. The relationships of the identified objects to DOM elements (e.g., tags) are determined, and the objects and related DOM elements are stored in training files. The training files are used to train various classifiers. Untagged PDF documents are then parsed to identify included visual objects, and the classifiers are used to determine DOM elements that should be associated with visual objects identified in the untagged PDF documents. This information is used to construct a DOM structure corresponding to each untagged document. A new PDF is then generated corresponding to each untagged document using the generated DOM structure and visual object information.
    Type: Grant
    Filed: May 1, 2023
    Date of Patent: October 15, 2024
    Assignee: OPEN TEXT CORPORATION
    Inventors: David Comeau, Jeffrey Williams, Evgeny Kolesnikov, Michael Itkin, June Qiang, James Relunia, Brian Sue
  • Publication number: 20230315974
    Abstract: Systems, methods, and products for auto tagging structured PDF documents that do not have accessibility tags. In one embodiment, structured PDF documents having accessibility tags are first parsed and analyzed to organize the visual components of the documents. The relationships of the identified objects to DOM elements (e.g., tags) are determined, and the objects and related DOM elements are stored in training files. The training files are used to train various classifiers. Untagged PDF documents are then parsed to identify included visual objects, and the classifiers are used to determine DOM elements that should be associated with visual objects identified in the untagged PDF documents. This information is used to construct a DOM structure corresponding to each untagged document. A new PDF is then generated corresponding to each untagged document using the generated DOM structure and visual object information.
    Type: Application
    Filed: May 1, 2023
    Publication date: October 5, 2023
    Inventors: David Comeau, Jeffrey Williams, Evgeny Kolesnikov, Michael Itkin, June Qiang, James Relunia, Brian Sue
  • Patent number: 11675970
    Abstract: Systems, methods, and products for auto tagging structured PDF documents that do not have accessibility tags. In one embodiment, structured PDF documents having accessibility tags are first parsed and analyzed to organize the visual components of the documents. The relationships of the identified objects to DOM elements (e.g., tags) are determined, and the objects and related DOM elements are stored in training files. The training files are used to train various classifiers. Untagged PDF documents are then parsed to identify included visual objects, and the classifiers are used to determine DOM elements that should be associated with visual objects identified in the untagged PDF documents. This information is used to construct a DOM structure corresponding to each untagged document. A new PDF is then generated corresponding to each untagged document using the generated DOM structure and visual object information.
    Type: Grant
    Filed: February 12, 2021
    Date of Patent: June 13, 2023
    Assignee: OPEN TEXT CORPORATION
    Inventors: David Comeau, Jeffrey Williams, Evgeny Kolesnikov, Michael Itkin, June Qiang, James Relunia, Brian Sue
  • Publication number: 20210271805
    Abstract: Systems, methods, and products for auto tagging structured PDF documents that do not have accessibility tags. In one embodiment, structured PDF documents having accessibility tags are first parsed and analyzed to organize the visual components of the documents. The relationships of the identified objects to DOM elements (e.g., tags) are determined, and the objects and related DOM elements are stored in training files. The training files are used to train various classifiers. Untagged PDF documents are then parsed to identify included visual objects, and the classifiers are used to determine DOM elements that should be associated with visual objects identified in the untagged PDF documents. This information is used to construct a DOM structure corresponding to each untagged document. A new PDF is then generated corresponding to each untagged document using the generated DOM structure and visual object information.
    Type: Application
    Filed: February 12, 2021
    Publication date: September 2, 2021
    Inventors: David Comeau, Jeffrey Williams, Evgeny Kolesnikov, Michael Itkin, June Qiang, James Relunia, Brian Sue