Patents by Inventor Gio Borje
Gio Borje 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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Patent number: 11429915Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: August 30, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 11010688Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: May 18, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 10679188Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: June 9, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 10521489Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: GrantFiled: November 30, 2017Date of Patent: December 31, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Patent number: 10467299Abstract: Systems and methods for identifying user information from a set of pages are disclosed. In example embodiments, a server determines that a first set of pages is associated with a specific user based on addresses of the first set of pages having a common portion of a uniform resource locator (URL). The server determines that at least a threshold number of pages from the first set of pages include common information, the common information comprising contact information or social networking information. The server associates the contact information or the social networking information with a user profile of the specific user. The server provides, as a digital transmission, the contact information or the social networking information.Type: GrantFiled: November 2, 2016Date of Patent: November 5, 2019Assignee: Microsoft Technology Licensing, LLCInventors: John Robert Jersin, Benjamin John McCann, Erik Eugene Buchanan, Gio Borje
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Patent number: 10423676Abstract: Systems and methods for identifying user information from a set of pages are disclosed. In example embodiments, a server determines that a first set of pages is associated with a specific user based on addresses of the first set of pages having a common portion of a uniform resource locator (URL). The server determines that at least a threshold number of pages from the first set of pages include common information, the common information comprising contact information or social networking information. The server associates the contact information or the social networking information with a user profile of the specific user. The server provides, as a digital transmission, the contact information or the social networking information.Type: GrantFiled: November 2, 2016Date of Patent: September 24, 2019Assignee: Microsoft Technology Licensing, LLCInventors: John Robert Jersin, Benjamin John McCann, Erik Eugene Buchanan, Gio Borje
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Publication number: 20190164132Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190163718Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190163668Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum
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Publication number: 20190164096Abstract: Systems and methods for predicting feature values in a matrix are disclosed. In example embodiments, a server accesses a matrix, the matrix having multiple dimensions, one dimension of the matrix representing features, and one dimension of the matrix representing entities. The server separates the matrix into multiple submatrices along a first dimension, each submatrix including all cells in the matrix for a set of values in the first dimension. The server provides the multiple submatrices to multiple machines. The server computes, using each machine, a correlation between values in at least one second dimension of the matrix and a value for a preselected feature in the matrix, the correlation being used to predict the value for the preselected feature based on other values along the at least one second dimension. The server provides an output representing the computed correlation.Type: ApplicationFiled: November 30, 2017Publication date: May 30, 2019Inventors: Gio Borje, Benjamin John McCann, David DiCato, Jerry Lin, Skylar Payne, Apoorv Khandelwal, Nadeem Anjum