Patents by Inventor Andrew K. McCallum

Andrew K. McCallum 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).

  • Method for learning and combining global and local regularities for information extraction and classification
    Patent number: 6892189
    Abstract: A method is provided for information extraction and classification which combines aspects of local regularities formulation with global regularities formulation. A candidate subset is identified. Then tentative labels are created so they can be associated with elements in the subset that have the global regularities, and the initial tentative labels are attached onto the identified elements of the candidate subset. The attached tentative labels are employed to formulate or “learn” initial local regularities. Further tentative labels are created so they can be associated with elements in the subset that have a combination of global and local regularities, and the further tentative labels are attached onto the identified elements of the candidate subset. Each new dataset is processed with reference to an increasingly-refined set of global regularities, and the output data with their associated confidence labels can be readily evaluated as to import and relevance.
    Type: Grant
    Filed: January 26, 2001
    Date of Patent: May 10, 2005
    Assignee: Inxight Software, Inc.
    Inventors: Dallan W. Quass, Tom M. Mitchell, Andrew K. McCallum, William Cohen
  • Method for learning and combining global and local regularities for information extraction and classification
    Publication number: 20020103775
    Abstract: A method is provided for information extraction and classification which combines aspects of local regularities formulation with global regularities formulation. A candidate subset is identified. Then tentative labels are created so they can be associated with elements in the subset that have the global regularities, and the initial tentative labels are attached onto the identified elements of the candidate subset. The attached tentative labels are employed to formulate or “learn” initial local regularities. Further tentative labels are created so they can be associated with elements in the subset that have a combination of global and local regularities, and the further tentative labels are attached onto the identified elements of the candidate subset. Each new dataset is processed with reference to an increasingly-refined set of global regularities, and the output data with their associated confidence labels can be readily evaluated as to import and relevance.
    Type: Application
    Filed: January 26, 2001
    Publication date: August 1, 2002
    Inventors: Dallan W. Quass, Tom M. Mitchell, Andrew K. McCallum, William Cohen