Patents by Inventor Daniel J. Rope
Daniel J. Rope 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: 11880778Abstract: A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.Type: GrantFiled: August 10, 2022Date of Patent: January 23, 2024Assignee: Cloud Software Group, Inc.Inventors: Thomas Hill, Michael O'Connell, Daniel J Rope
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Patent number: 11651233Abstract: According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.Type: GrantFiled: February 11, 2020Date of Patent: May 16, 2023Assignee: International Business Machines CorporationInventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Publication number: 20220383163Abstract: A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.Type: ApplicationFiled: August 10, 2022Publication date: December 1, 2022Applicant: TIBCO Software Inc.Inventors: Thomas HILL, Michael O'CONNELL, Daniel J ROPE
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Patent number: 11443206Abstract: A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.Type: GrantFiled: January 23, 2020Date of Patent: September 13, 2022Assignee: TIBCO Software Inc.Inventors: Thomas Hill, Michael O'Connell, Daniel J Rope
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Patent number: 11429623Abstract: An apparatus for estimating analytics and interactive exploration of big data, stored and/or streaming, using approximate query processing is presented. The apparatus comprises a model constructor and a sampler. The model constructor identifies important predictors variables in big data using feature selection, predictor variables, and outcome variables and partitions the important predictor variables into one or more stratifications based either the identified interactions or identified relationships. The sampler generates a subset of data by querying the big data using a query constructed based on at least one stratification. The subset of data can be fed into an analytics generator. The analytics generator generates analytics data for the outcome variables based on the subset of data and an analytics algorithm and a visualization, e.g. an interactive visualization, comprising the outcome variables, the important predictor variables, the stratification, the subset of data, and the analytics data.Type: GrantFiled: January 9, 2020Date of Patent: August 30, 2022Assignee: TIBCO Software Inc.Inventors: Thomas Hill, David Katz, Michael O'Connell, Jags Ramnarayan, Daniel J. Rope
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Patent number: 11068647Abstract: System, method, and computer program product for measuring transitions between visualizations, the method comprising identifying data fields represented in a first visualization and one or more presentation characteristics for the data fields represented in the first visualization, identifying data fields represented in a second visualization and one or more presentation characteristics for the data fields represented in the second visualization, determining a plurality of transition scores, wherein each transition score represents a difference or similarity between the first and second visualizations, relative to either the identified data fields or the presentation characteristics, and generating a composite measure of transition between the first and second visualizations from the plurality of transition scores.Type: GrantFiled: May 28, 2015Date of Patent: July 20, 2021Assignee: International Business Machines CorporationInventors: Thomas A. Keahey, Daniel J. Rope, Graham J. Wills
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Publication number: 20210216544Abstract: An apparatus for estimating analytics and interactive exploration of big data, stored and/or streaming, using approximate query processing is presented. The apparatus comprises a model constructor and a sampler. The model constructor identifies important predictors variables in big data using feature selection, predictor variables, and outcome variables and partitions the important predictor variables into one or more stratifications based either the identified interactions or identified relationships. The sampler generates a subset of data by querying the big data using a query constructed based on at least one stratification. The subset of data can be fed into an analytics generator. The analytics generator generates analytics data for the outcome variables based on the subset of data and an analytics algorithm and a visualization, e.g. an interactive visualization, comprising the outcome variables, the important predictor variables, the stratification, the subset of data, and the analytics data.Type: ApplicationFiled: January 9, 2020Publication date: July 15, 2021Inventors: Thomas HILL, David KATZ, Michael O'CONNELL, Jags RAMNARAYAN, Daniel J. ROPE
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Publication number: 20210157819Abstract: A set of transition characteristics can be identified. The set of transition characteristics can include continuities and discontinuities between data fields and data visualization channels among a plurality of data visualizations. A transition tuple for each of a plurality of pairs of the data visualizations can be determined and mapped to a matrix. The matrix can be transposed to generate vectors, each vector representing a type of transition characteristic, at least one of the vectors comprising a plurality of elements equaling a total number of the determined transition tuples. The distribution of the data fields and the data visualization channels across the data visualizations can be determined by performing statistical analysis on each of the vectors. A collection of the data visualizations can be determined based on the statistical analysis performed on each of the vectors, the collection of the data visualizations can include a subset of the data visualizations.Type: ApplicationFiled: February 3, 2021Publication date: May 27, 2021Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Publication number: 20210103832Abstract: A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.Type: ApplicationFiled: January 23, 2020Publication date: April 8, 2021Inventors: Thomas HILL, Michael O'CONNELL, Daniel J. ROPE
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Patent number: 10949444Abstract: A set of transition characteristics can be identified. The set of transition characteristics can include continuities and discontinuities between data fields and data visualization channels among a plurality of data visualizations. The set of transition characteristics can be identified by analyzing the plurality of data visualizations and identifying similarities and differences among the data fields and the data visualization channels. A distribution of the data fields and the data visualization channels across the plurality of data visualizations can be determined. A collection of the data visualizations can be determined based on the distribution of the data fields and the data visualization channels across the plurality of data visualizations. The collection of the data visualizations can include at least a subset of the plurality of data visualizations.Type: GrantFiled: January 30, 2018Date of Patent: March 16, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Patent number: 10776569Abstract: A data portion of a data set utilized in a computerized visualization is analyzed to identify one or more areas of interest each including data values representing distinguishable features relative to the data set. An explanation for the data values of each of the one or more areas of interest is determined. Each explanation is based on other data portions of the data set contributing to the distinguishable features. At least one display layer including labels describing the one or more areas of interest is generated. The labels include the explanation for each of the one or more areas of interest. The at least one display layer is disposed over the computerized visualization to produce an annotated visualization with the labels positioned proximate the one or more areas of interest.Type: GrantFiled: July 29, 2016Date of Patent: September 15, 2020Assignee: International Business Machines CorporationInventors: Marc S. Altshuller, Daniel J. Rope, Jing-Yun Shyr, Devendra G. Tasgaonkar, Graham J. Wills
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Patent number: 10769162Abstract: Techniques are described for genomically defining digital genes encoding data visualization elements and potential incremental changes to the elements as the basis for a genetic selection process for automated generating of data visualizations. In one aspect, a method includes receiving set of input data. The method further includes generating digital genes that genomically define data visualization elements based on the input data, and that define potential incremental changes to the data visualization elements. The method further includes executing a genetic selection process with respect to one or more fitness functions on populations of candidate data visualizations that are based on the genomically defined data visualization elements. The method further includes outputting final data visualization output generated by the genetic selection process.Type: GrantFiled: March 16, 2017Date of Patent: September 8, 2020Assignee: International Business Machines CorporationInventors: Daniel J. Rope, Graham J. Wills
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Patent number: 10769161Abstract: Techniques are described for genomically defining digital genes encoding data visualization elements and potential incremental changes to the elements as the basis for a genetic selection process for automated generating of data visualizations. In one aspect, a method includes receiving set of input data. The method further includes generating digital genes that genomically define data visualization elements based on the input data, and that define potential incremental changes to the data visualization elements. The method further includes executing a genetic selection process with respect to one or more fitness functions on populations of candidate data visualizations that are based on the genomically defined data visualization elements. The method further includes outputting final data visualization output generated by the genetic selection process.Type: GrantFiled: November 3, 2015Date of Patent: September 8, 2020Assignee: International Business Machines CorporationInventors: Daniel J. Rope, Graham J. Wills
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Patent number: 10685035Abstract: A set of transition characteristics can be identified. The set of transition characteristics can include continuities and discontinuities between data fields and data visualization channels among a plurality of data visualizations. The set of transition characteristics can be identified by analyzing the plurality of data visualizations and identifying similarities and differences among the data fields and the data visualization channels. A distribution of the data fields and the data visualization channels across the plurality of data visualizations can be determined. A collection of the data visualizations can be determined based on the distribution of the data fields and the data visualization channels across the plurality of data visualizations. The collection of the data visualizations can include at least a subset of the plurality of data visualizations.Type: GrantFiled: June 30, 2016Date of Patent: June 16, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Publication number: 20200175381Abstract: According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.Type: ApplicationFiled: February 11, 2020Publication date: June 4, 2020Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Patent number: 10607139Abstract: According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.Type: GrantFiled: September 23, 2015Date of Patent: March 31, 2020Assignee: International Business Machines CorporationInventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Patent number: 10599979Abstract: According to one embodiment, a method for generating a plurality of candidate visualizations. The method may include receiving a scenario description. The method may also include collecting a plurality of expert data using a training system based on the received scenario description. The method may further include generating at least one predictive model based on the collected plurality of expert data in order to execute the at least one generated predictive model during an application of a plurality of genetic algorithms.Type: GrantFiled: April 6, 2017Date of Patent: March 24, 2020Assignee: International Business Machines CorporationInventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
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Patent number: 10565035Abstract: A method, system, and/or computer program product modify a hardware device based on a time series of data. One or more processors standardize a time series of data received from sensors that are monitoring a hardware device. The processor(s) establish time ranges before, during and after each event. The processor(s) determine which events represented by the time series of data are significant by comparing means and trends of time sub-series corresponding to the time ranges before, during, and after each event, and then generate a modified time series of data by reducing a number of significant events described by the time series of data, which is used to modify the hardware device.Type: GrantFiled: December 11, 2018Date of Patent: February 18, 2020Assignee: International Business Machines CorporationInventors: Daniel J. Rope, Graham J. Wills
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Patent number: 10395215Abstract: Provided are techniques for summarizing statistical results. Multiple sets of statistical results are received, wherein each of the sets of statistical results are ordered according to interestingness. Insights are generated based on the multiple sets of statistical results. Relationships between the generated insights are identified. An executive summary is generated with a set of findings based on the identified relationships. An interactive visualization is provided with the generated insights based on the executive summary.Type: GrantFiled: October 19, 2012Date of Patent: August 27, 2019Assignee: International Business Machines CorporationInventors: Daniel J. Rope, Jing-Yun Shyr, Margaret J. Vais, Michael D. Woods
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Publication number: 20190122122Abstract: A predictive engine for interpreting data structures that includes an interpreter and visualization generator. The interpreter identifies a relational pattern between target feature variables and other feature variables based on recognizing a variable dependency between the target feature data and the other feature data and generate at least one meta-data feature set and associated result metrics. The visualization generator can recommend at least one visualization based on the at least one meta-data feature set and the associated result metrics. The interpreter includes multiple stages that perform variable selection, interaction detection, and pattern discovery and ranking. The predictive engine also includes a data preparer configured to sort, categorize, and filter the data structures according to at least one of data type, hierarchical data structures, unique values, missing values and date/time data.Type: ApplicationFiled: October 23, 2018Publication date: April 25, 2019Inventors: Daniel J. ROPE, Andrew J. BERRIDGE, Michael O'CONNELL, Gaia Valeria PAOLINI, DivyaJyoti Pitamberlal RAJDEV