Patents by Inventor Tracy D. Lemmond

Tracy D. Lemmond 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: 8725666
    Abstract: An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.
    Type: Grant
    Filed: February 28, 2011
    Date of Patent: May 13, 2014
    Assignee: Lawrence Livermore National Security, LLC.
    Inventors: Tracy D. Lemmond, William G. Hanley, Joseph Wendell Guensche, Nathan C. Perry, John J. Nitao, Paul Brandon Kidwell, Kofi Agyeman Boakye, Ron E. Glaser, Ryan James Prenger
  • Patent number: 8306942
    Abstract: A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.
    Type: Grant
    Filed: May 6, 2009
    Date of Patent: November 6, 2012
    Assignee: Lawrence Livermore National Security, LLC
    Inventors: Barry Y. Chen, William G. Hanley, Tracy D. Lemmond, Lawrence J. Hiller, David A. Knapp, Marshall J. Mugge
  • Publication number: 20110213742
    Abstract: An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.
    Type: Application
    Filed: February 28, 2011
    Publication date: September 1, 2011
    Inventors: Tracy D. LEMMOND, William G. HANLEY, Joseph Wendell GUENSCHE, Nathan C. PERRY, John J. NITAO, Paul Brandon KIDWELL, Kofi Agyeman BOAKYE, Ronald E. GLASER, Ryan James PRENGER
  • Publication number: 20090281981
    Abstract: A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.
    Type: Application
    Filed: May 6, 2009
    Publication date: November 12, 2009
    Inventors: Barry Y. Chen, William G. Hanley, Tracy D. Lemmond, Lawrence J. Hiller, David A. Knapp, Marshall J. Mugge