Patents by Inventor Khosrow M Hassibi

Khosrow M Hassibi 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).

  • Detecting and measuring risk with predictive models using content mining
    Patent number: 8032448
    Abstract: Computer implemented methods and systems of processing transactions to determine the risk of transaction convert high categorical information, such as text data, to low categorical information, such as category or cluster IDs. The text data may be merchant names or other textual content of the transactions, or data related to a consumer, or any other type of entity which engages in the transaction. Content mining techniques are used to provide the conversion from high to low categorical information. In operation, the resulting low categorical information is input, along with other data, into a statistical model. The statistical model provides an output of the level of risk in the transaction. Methods of converting the high categorical information to low categorical clusters, of using such information, and other aspects of the use of such clusters are disclosed.
    Type: Grant
    Filed: October 4, 2007
    Date of Patent: October 4, 2011
    Assignee: Fair Isaac Corporation
    Inventors: Russell Anderson, Larry S. Peranich, Ricardo M. Dungca, Joseph P. Milana, Xuhui Shao, Paul C. Dulany, Khosrow M. Hassibi, James C. Baker
  • Detecting and Measuring Risk with Predictive Models Using Content Mining
    Publication number: 20090234683
    Abstract: Computer implemented methods and systems of processing transactions to determine the risk of transaction convert high categorical information, such as text data, to low categorical information, such as category or cluster IDs. The text data may be merchant names or other textual content of the transactions, or data related to a consumer, or any other type of entity which engages in the transaction. Content mining techniques are used to provide the conversion from high to low categorical information. In operation, the resulting low categorical information is input, along with other data, into a statistical model. The statistical model provides an output of the level of risk in the transaction. Methods of converting the high categorical information to low categorical clusters, of using such information, and other aspects of the use of such clusters are disclosed.
    Type: Application
    Filed: October 4, 2007
    Publication date: September 17, 2009
    Inventors: Russell Anderson, Larry S. Peranich, Ricardo M. Dungca, Joseph P. Milana, Xuhui Shao, Paul C. Dulany, Khosrow M. Hassibi, James C. Baker
  • Detecting and measuring risk with predictive models using content mining
    Patent number: 7376618
    Abstract: Computer implemented methods and systems of processing transactions to determine the risk of transaction convert high categorical information, such as text data, to low categorical information, such as category or cluster IDs. The text data may be merchant names or other textual content of the transactions, or data related to a consumer, or any other type of entity which engages in the transaction. Content mining techniques are used to provide the conversion from high to low categorical information. In operation, the resulting low categorical information is input, along with other data, into a statistical model. The statistical model provides an output of the level of risk in the transaction. Methods of converting the high categorical information to low categorical clusters, of using such information, and other aspects of the use of such clusters are disclosed.
    Type: Grant
    Filed: September 29, 2000
    Date of Patent: May 20, 2008
    Assignee: Fair Isaac Corporation
    Inventors: Russell Anderson, Larry S Peranich, Ricardo Dungca, Joseph P Milana, Xuhui Shao, Paul C Dulany, Khosrow M Hassibi, James C Baker