Patents by Inventor Glenn Allen Murray
Glenn Allen Murray 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: 11704321Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.Type: GrantFiled: March 23, 2020Date of Patent: July 18, 2023Assignee: Oracle International CorporationInventors: Robert James Oberbreckling, Luis E. Rivas, Michael Malak, Glenn Allen Murray
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Patent number: 11500880Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.Type: GrantFiled: January 25, 2021Date of Patent: November 15, 2022Assignee: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas, Mark L. Kreider
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Patent number: 11379506Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.Type: GrantFiled: December 31, 2018Date of Patent: July 5, 2022Assignee: Oracle International CorporationInventors: Alexander Sasha Stojanovic, Mark Kreider, Michael Malak, Glenn Allen Murray
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Patent number: 11200248Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.Type: GrantFiled: December 31, 2019Date of Patent: December 14, 2021Assignee: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas
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Publication number: 20210149907Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.Type: ApplicationFiled: January 25, 2021Publication date: May 20, 2021Applicant: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas, Mark L. Kreider
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Patent number: 10936599Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.Type: GrantFiled: September 25, 2018Date of Patent: March 2, 2021Assignee: Oracle International CorporationInventors: Glenn Allen Murray, Luis E Rivas, Mark L. Kreider
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Patent number: 10891272Abstract: The present disclosure relates generally to a data enrichment service that extracts, repairs, and enriches datasets, resulting in more precise entity resolution and correlation for purposes of subsequent indexing and clustering. As the data enrichment service can include a visual recommendation engine and language for performing large-scale data preparation, repair, and enrichment of heterogeneous datasets. This enables the user to select and see how the recommended enrichments (e.g., transformations and repairs) will affect the user's data and make adjustments as needed. The data enrichment service can receive feedback from users through a user interface and can filter recommendations based on the user feedback.Type: GrantFiled: September 24, 2015Date of Patent: January 12, 2021Assignee: ORACLE INTERNATIONAL CORPORATIONInventors: Alexander Sasha Stojanovic, Luis E. Rivas, Philip Ogren, Glenn Allen Murray
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Publication number: 20200242111Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.Type: ApplicationFiled: March 23, 2020Publication date: July 30, 2020Applicant: Oracle International CorporationInventors: Robert James Oberbreckling, Luis E. Rivas, Michael Malak, Glenn Allen Murray
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Publication number: 20200210417Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.Type: ApplicationFiled: December 31, 2019Publication date: July 2, 2020Applicant: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas
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Patent number: 10650000Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.Type: GrantFiled: September 14, 2017Date of Patent: May 12, 2020Assignee: Oracle International CorporationInventors: Robert James Oberbreckling, Luis E. Rivas, Michael Malak, Glenn Allen Murray
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Patent number: 10565222Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.Type: GrantFiled: September 14, 2017Date of Patent: February 18, 2020Assignee: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas
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Publication number: 20190138538Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.Type: ApplicationFiled: December 31, 2018Publication date: May 9, 2019Applicant: Oracle International CorporationInventors: Alexander Sasha Stojanovic, Mark Kreider, Michael Malak, Glenn Allen Murray
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Publication number: 20190102438Abstract: Techniques are disclosed for providing adaptive recommendations for a data set. A data set can include one or more columns of data. The data set can be profiled in order to identify actions that can be applied to the data in order to enrich the data. The data set and actions that were applied to the data set can be stored. Actions that are applied to subsequent data sets can take into account the actions that were applied to prior data sets having similar profiles.Type: ApplicationFiled: September 25, 2018Publication date: April 4, 2019Applicant: Oracle International CorporationInventors: Glenn Allen Murray, Luis E Rivas, Mark L. Kreider
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Patent number: 10210246Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.Type: GrantFiled: September 24, 2015Date of Patent: February 19, 2019Assignee: Oracle International CorporationInventors: Alexander Sasha Stojanovic, Mark Kreider, Michael Malak, Glenn Allen Murray
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Publication number: 20180075104Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.Type: ApplicationFiled: September 14, 2017Publication date: March 15, 2018Applicant: Oracle International CorporationInventors: Robert James Oberbreckling, Luis E. Rivas, Michael Malak, Glenn Allen Murray
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Publication number: 20180075115Abstract: Techniques are disclosed for a system that provides an intuitive way for merging or joining data from different datasets. The system may provide graphical interfaces to enable a user to combine or join datasets identified as having a relationship. In at least one embodiment, the system can determine options for joining datasets, such as by a left join, right join, or outer join. A graphical interface may display a visual representation (e.g., a “Glenn Diagram”) illustrate options for joining datasets based on identifying a relationship between the data sets. The representation may further illustrate one or more types of joins and information about the data, such as rows where data may be joined based on the type of join function for the relationship by columns. The visual representation may indicate where the datasets can be joined, such that they are not overlapping.Type: ApplicationFiled: September 14, 2017Publication date: March 15, 2018Applicant: Oracle International CorporationInventors: Glenn Allen Murray, Luis E. Rivas
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Publication number: 20160092557Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.Type: ApplicationFiled: September 24, 2015Publication date: March 31, 2016Inventors: Alexander Sasha Stojanovic, Mark Kreider, Michael Malak, Glenn Allen Murray
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Publication number: 20160092474Abstract: The present disclosure relates generally to a data enrichment service that extracts, repairs, and enriches datasets, resulting in more precise entity resolution and correlation for purposes of subsequent indexing and clustering. As the data enrichment service can include a visual recommendation engine and language for performing large-scale data preparation, repair, and enrichment of heterogeneous datasets. This enables the user to select and see how the recommended enrichments (e.g., transformations and repairs) will affect the user's data and make adjustments as needed. The data enrichment service can receive feedback from users through a user interface and can filter recommendations based on the user feedback.Type: ApplicationFiled: September 24, 2015Publication date: March 31, 2016Inventors: Alexander Sasha Stojanovic, Luis E. Rivas, Philip Ogren, Glenn Allen Murray