Patents by Inventor Debora L. Nascimento Ciriaco Pereira

Debora L. Nascimento Ciriaco Pereira 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).

  • CONTEXTUAL TEXT ADAPTATION
    Publication number: 20170178028
    Abstract: Contextual adaptation of documents automatically replaces words for synonyms that appear within context or topic whey they are being used. A machine learned topic modeling, trained by a set of documents representative of a target user is executed to determine topics of an input document, and to determine words in the document to replace based on determining the relevance of the words to the topics in the documents. An output document is generated based on the input document with the replaced words.
    Type: Application
    Filed: August 2, 2016
    Publication date: June 22, 2017
    Inventors: Carlos H. Cardonha, Stefany Mazon, Debora L. Nascimento Ciriaco Pereira, Nicole B. Sultanum
  • Contextual text adaptation
    Patent number: 9672476
    Abstract: Contextual adaptation of documents automatically replaces words for synonyms that appear within context or topic whey they are being used. A machine learned topic modeling, trained by a set of documents representative of a target user is executed to determine topics of an input document, and to determine words in the document to replace based on determining the relevance of the words to the topics in the documents. An output document is generated based on the input document with the replaced words.
    Type: Grant
    Filed: August 2, 2016
    Date of Patent: June 6, 2017
    Assignee: International Business Machines Corporation
    Inventors: Carlos H. Cardonha, Stefany Mazon, Debora L. Nascimento Ciriaco Pereira, Nicole B. Sultanum
  • Contextual text adaptation
    Patent number: 9519871
    Abstract: Contextual adaptation of documents automatically replaces words for synonyms that appear within context or topic whey they are being used. A machine learned topic modeling, trained by a set of documents representative of a target user is executed to determine topics of an input document, and to determine words in the document to replace based on determining the relevance of the words to the topics in the documents. An output document is generated based on the input document with the replaced words.
    Type: Grant
    Filed: December 21, 2015
    Date of Patent: December 13, 2016
    Assignee: International Business Machines Corporation
    Inventors: Carlos H. Cardonha, Stefany Mazon, Debora L. Nascimento Ciriaco Pereira, Nicole B. Sultanum