Patents by Inventor Chetan K. Kotak

Chetan K. Kotak 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).

  • INFORMATION FUSION FOR MULTIPLE ANOMALY DETECTION SYSTEMS
    Publication number: 20110213788
    Abstract: The present invention is a method for detecting anomalies against normal profiles and for fusing and visualizing the results from multiple anomaly detection systems in a quantifying and unifying user interface. The knowledge patterns discovered from historical data serve as the normal profiles, or baselines or references (hereinafter, called “normal profiles”). The method assesses a piece of information against a collection of the normal profiles and decides how anomalous it is. The normal profiles are calculated from historical data sources, and stored in a collection of mining models. Multiple anomaly detection systems generate a collection of mining models using multiple data sources. When a piece of information is newly observed, the method measures the degree of correlation between the observed information and the normal profiles.
    Type: Application
    Filed: May 9, 2011
    Publication date: September 1, 2011
    Applicant: QUANTUM INTELLIGENCE, INC.
    Inventors: YING ZHAO, Charles Chuxin Zhou, Chetan K. Kotak
  • FUSION AND VISUALIZATION FOR MULTIPLE ANOMALY DETECTION SYSTEMS
    Publication number: 20080215576
    Abstract: The present invention is a method for detecting anomalies against normal profiles and for fusing and visualizing the results from multiple anomaly detection systems in a quantifying and unifying user interface. The knowledge patterns discovered from historical data serve as the normal profiles, or baselines or references (hereinafter, called “normal profiles”). The method assesses a piece of information against a collection of the normal profiles and decides how anomalous it is. The normal profiles are calculated from historical data sources, and stored in a collection of mining models. Multiple anomaly detection systems generate a collection of mining models using multiple data sources. When a piece of information is newly observed, the method measures the degree of correlation between the observed information and the normal profiles.
    Type: Application
    Filed: March 5, 2008
    Publication date: September 4, 2008
    Applicant: QUANTUM INTELLIGENCE, INC.
    Inventors: Ying Zhao, Charles Chuxin Zhou, Chetan K. Kotak