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).
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Publication number: 20150012337Abstract: 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: ApplicationFiled: July 14, 2014Publication date: January 8, 2015Inventors: Michael W. Kruger, Romesh Wadhwani
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Patent number: 8781877Abstract: 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: GrantFiled: February 29, 2012Date of Patent: July 15, 2014Assignee: Information Resources, Inc.Inventors: Michael W. Kruger, Romesh Wadhwani
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Patent number: 8589208Abstract: 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: GrantFiled: November 18, 2011Date of Patent: November 19, 2013Assignee: Information Resources, Inc.Inventors: Michael W. Kruger, Romesh Wadhwani
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Publication number: 20120158460Abstract: 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: ApplicationFiled: February 29, 2012Publication date: June 21, 2012Inventors: Michael W. Kruger, Romesh Wadhwani
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Publication number: 20120150587Abstract: 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: ApplicationFiled: November 18, 2011Publication date: June 14, 2012Inventors: Michael W. Kruger, Romesh Wadhwani
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Patent number: 7873529Abstract: 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: GrantFiled: February 20, 2004Date of Patent: January 18, 2011Assignee: SymphonyIRI Group, Inc.Inventors: Michael W. Kruger, Cheryl G. Bergeon, Arvid C. Johnson
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Publication number: 20080256027Abstract: 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: ApplicationFiled: October 29, 2007Publication date: October 16, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080256028Abstract: 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: ApplicationFiled: October 29, 2007Publication date: October 16, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080168027Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 10, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080168104Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 10, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080168028Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 10, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162404Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162572Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162461Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: Michael W. Kruger, Cheryl G. Bergeon, Arvid C. Johnson
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Publication number: 20080162462Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162464Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: Michael W. Kruger, Cheryl G. Bergeon, Arvid C. Johnson
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Publication number: 20080162465Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162460Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162223Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON
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Publication number: 20080162463Abstract: 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: ApplicationFiled: October 29, 2007Publication date: July 3, 2008Inventors: MICHAEL W. KRUGER, CHERYL G. BERGEON, ARVID C. JOHNSON