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).

  • Patent number: 11880778
    Abstract: 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: Grant
    Filed: August 10, 2022
    Date of Patent: January 23, 2024
    Assignee: Cloud Software Group, Inc.
    Inventors: Thomas Hill, Michael O'Connell, Daniel J Rope
  • Patent number: 11651233
    Abstract: 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: Grant
    Filed: February 11, 2020
    Date of Patent: May 16, 2023
    Assignee: International Business Machines Corporation
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Publication number: 20220383163
    Abstract: 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: Application
    Filed: August 10, 2022
    Publication date: December 1, 2022
    Applicant: TIBCO Software Inc.
    Inventors: Thomas HILL, Michael O'CONNELL, Daniel J ROPE
  • Patent number: 11443206
    Abstract: 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: Grant
    Filed: January 23, 2020
    Date of Patent: September 13, 2022
    Assignee: TIBCO Software Inc.
    Inventors: Thomas Hill, Michael O'Connell, Daniel J Rope
  • Patent number: 11429623
    Abstract: 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: Grant
    Filed: January 9, 2020
    Date of Patent: August 30, 2022
    Assignee: TIBCO Software Inc.
    Inventors: Thomas Hill, David Katz, Michael O'Connell, Jags Ramnarayan, Daniel J. Rope
  • Patent number: 11068647
    Abstract: 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: Grant
    Filed: May 28, 2015
    Date of Patent: July 20, 2021
    Assignee: International Business Machines Corporation
    Inventors: Thomas A. Keahey, Daniel J. Rope, Graham J. Wills
  • Publication number: 20210216544
    Abstract: 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: Application
    Filed: January 9, 2020
    Publication date: July 15, 2021
    Inventors: Thomas HILL, David KATZ, Michael O'CONNELL, Jags RAMNARAYAN, Daniel J. ROPE
  • Publication number: 20210157819
    Abstract: 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: Application
    Filed: February 3, 2021
    Publication date: May 27, 2021
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Publication number: 20210103832
    Abstract: 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: Application
    Filed: January 23, 2020
    Publication date: April 8, 2021
    Inventors: Thomas HILL, Michael O'CONNELL, Daniel J. ROPE
  • Patent number: 10949444
    Abstract: 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: Grant
    Filed: January 30, 2018
    Date of Patent: March 16, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Patent number: 10776569
    Abstract: 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: Grant
    Filed: July 29, 2016
    Date of Patent: September 15, 2020
    Assignee: International Business Machines Corporation
    Inventors: Marc S. Altshuller, Daniel J. Rope, Jing-Yun Shyr, Devendra G. Tasgaonkar, Graham J. Wills
  • Patent number: 10769162
    Abstract: 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: Grant
    Filed: March 16, 2017
    Date of Patent: September 8, 2020
    Assignee: International Business Machines Corporation
    Inventors: Daniel J. Rope, Graham J. Wills
  • Patent number: 10769161
    Abstract: 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: Grant
    Filed: November 3, 2015
    Date of Patent: September 8, 2020
    Assignee: International Business Machines Corporation
    Inventors: Daniel J. Rope, Graham J. Wills
  • Patent number: 10685035
    Abstract: 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: Grant
    Filed: June 30, 2016
    Date of Patent: June 16, 2020
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Publication number: 20200175381
    Abstract: 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: Application
    Filed: February 11, 2020
    Publication date: June 4, 2020
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Patent number: 10607139
    Abstract: 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: Grant
    Filed: September 23, 2015
    Date of Patent: March 31, 2020
    Assignee: International Business Machines Corporation
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Patent number: 10599979
    Abstract: 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: Grant
    Filed: April 6, 2017
    Date of Patent: March 24, 2020
    Assignee: International Business Machines Corporation
    Inventors: T. Alan Keahey, Daniel J. Rope, Graham J. Wills
  • Patent number: 10565035
    Abstract: 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: Grant
    Filed: December 11, 2018
    Date of Patent: February 18, 2020
    Assignee: International Business Machines Corporation
    Inventors: Daniel J. Rope, Graham J. Wills
  • Patent number: 10395215
    Abstract: 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: Grant
    Filed: October 19, 2012
    Date of Patent: August 27, 2019
    Assignee: International Business Machines Corporation
    Inventors: Daniel J. Rope, Jing-Yun Shyr, Margaret J. Vais, Michael D. Woods
  • Publication number: 20190122122
    Abstract: 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: Application
    Filed: October 23, 2018
    Publication date: April 25, 2019
    Inventors: Daniel J. ROPE, Andrew J. BERRIDGE, Michael O'CONNELL, Gaia Valeria PAOLINI, DivyaJyoti Pitamberlal RAJDEV