Patents by Inventor Michael W. Kruger

Michael W. Kruger 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).

  • Publication number: 20150012337
    Abstract: Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behavioral propensities for the population at an individual or household level.
    Type: Application
    Filed: July 14, 2014
    Publication date: January 8, 2015
    Inventors: Michael W. Kruger, Romesh Wadhwani
  • Patent number: 8781877
    Abstract: Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behavioral propensities for the population at an individual or household level.
    Type: Grant
    Filed: February 29, 2012
    Date of Patent: July 15, 2014
    Assignee: Information Resources, Inc.
    Inventors: Michael W. Kruger, Romesh Wadhwani
  • Patent number: 8589208
    Abstract: Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behaviorial propensities for the population at an individual or household level.
    Type: Grant
    Filed: November 18, 2011
    Date of Patent: November 19, 2013
    Assignee: Information Resources, Inc.
    Inventors: Michael W. Kruger, Romesh Wadhwani
  • Publication number: 20120158460
    Abstract: Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behavioral propensities for the population at an individual or household level.
    Type: Application
    Filed: February 29, 2012
    Publication date: June 21, 2012
    Inventors: Michael W. Kruger, Romesh Wadhwani
  • Publication number: 20120150587
    Abstract: Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behaviorial propensities for the population at an individual or household level.
    Type: Application
    Filed: November 18, 2011
    Publication date: June 14, 2012
    Inventors: Michael W. Kruger, Romesh Wadhwani
  • Patent number: 7873529
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Grant
    Filed: February 20, 2004
    Date of Patent: January 18, 2011
    Assignee: SymphonyIRI Group, Inc.
    Inventors: Michael W. Kruger, Cheryl G. Bergeon, Arvid C. Johnson
  • Publication number: 20080256027
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: October 16, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080256028
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: October 16, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080168028
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 10, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080168027
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 10, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080168104
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 10, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162571
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162404
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162462
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162466
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162461
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: Michael W. Kruger, Cheryl G. Bergeon, Arvid C. Johnson
  • Publication number: 20080162223
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162463
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162460
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
  • Publication number: 20080162572
    Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.
    Type: Application
    Filed: October 29, 2007
    Publication date: July 3, 2008
    Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON