Method and system for presenting statistical data in a natural language format

• US 9,792,283 B2
• Filed: 07/19/2016
• Issued: 10/17/2017
• Est. Priority Date: 09/27/2013
• Status: Active Grant

• Current Assignee: Intellectus Statistics LLC
• Original Assignee: Intellectus Statistics LLC
• Inventors: Lani, James A., Moran, Melissa
• Primary Examiner(s): Dorvil, Richemond
• Assistant Examiner(s): BLANKENAGEL, BRYAN S
• Application Number:
  US15/213,464
• Publication Number:
  US 20160328395A1
• Time in Patent Office: 455 Days
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06F 40/106 Display of layout of documents; Previewing
• CPC Class Codes: G06F 40/174 Form filling; Merging
• CPC Class Codes: G06F 40/216 using statistical methods
• CPC Class Codes: G06F 40/56 Natural language generation

Abstract

A computer-implemented method for presenting statistical analysis in a natural language textual output comprising: receiving data to be analyzed by the processor; processing the data according to at least one of a plurality of pre-established statistical analysis types, thereby providing processed data; interpreting the processed data by analyzing the processed data to provide a pre-determined natural language text, thereby providing interpreted data; and generating a natural language textual output for the interpreted data according to at least one pre-established rule for converting the interpreted data to a natural language textual output.

Claims

1. A computer-implemented method for presenting statistical analysis findings in a natural language textual output, the computer-implemented method employing a processor and comprising:

providing pre-established plain language descriptive text;

providing a plurality of pre-established statistical analysis types, wherein the analysis types include at least one of inferential statistical analyses, non-parametric analysis, data mining analyses (association rules, neural networks, generalized additive models, classification and regression trees, predictive models, CHAID models, cluster analyses, data reduction, classification models), supervised and unsupervised models, time series models, structural equation models, medical informatics, bioinformatics, and fraud detection models;

selecting at least one of the plurality of pre-established statistical analysis types;

aligning the at least one of the plurality of pre-established statistical analysis types with at least a portion of the pre-established plain language descriptive text;

receiving data to be analyzed by the processor through a secure login module, wherein the data comprises at least one of numerals and parameters;

organizing the data to permit the data to be analyzed in accordance with the selected pre-established statistical analysis type, thereby providing organized data;

processing the organized data according to the selected pre-established statistical analysis type, wherein the processing is performed by a statistical analysis tool for providing processed data and wherein if the data is not statistically appropriate for the selected pre-established statistical type, replacing the pre-established plain language descriptive text with informative text explaining the data is not appropriate for the selected pre-established statistical type;

interpreting the processed data by converting the processed data to a pre-determined natural language text, thereby providing interpreted data;

using one of the pre-established statistical analysis types, determining whether the interpreted data should be processed with a second pre-established statistical analysis type, wherein the second pre-established statistical analysis type is not the previously selected pre-established statistical type;

generating a natural language textual output for the interpreted data according to at least one pre-established rule, the at least one pre-established rule comprising;

dynamically merging at least a portion of the pre-established plain language descriptive text with the natural language text using at least one of the pre-established statistical analysis wherein the output may further comprise at least one graphic display, and wherein the graphic display is selected from the group consisting of a table, a chart, and a graph; and

providing the natural language textual output in a computer file, wherein a computer displays the natural language textual output in a formatted word processing document.

2. A computer-implemented method for presenting statistical analysis in a natural language textual output, the computer-implemented method employing a processor and comprising:

receiving data to be analyzed by the processor through a secure login module;

processing the data according to at least one of a plurality of pre-established statistical analysis types, thereby providing processed data;

interpreting the processed data and converting the processed data to a pre-determined natural language text, thereby providing interpreted data;

using one of the pre-established statistical analysis types, determining whether the interpreted data should be processed with a second pre-established statistical analysis type, wherein the second pre-established statistical analysis type is not the pre-established statistical type previously selected used to process the data;

generating a natural language textual output for the dynamically interpreted data according to at least one pre-established rule for converting the interpreted data to a natural language textual output; and

providing the natural language textual output in a computer file, wherein a computer displays the natural language textual output in a formatted word processing document.

3. The method according to claim 2, further comprising providing pre-established plain language descriptive text and aligning at least one of a plurality of statistical analysis types with at least a portion of the pre-established plain language descriptive text.

4. The method according to claim 3, wherein the plurality of pre-established statistical analysis types include at least one of inferential statistical analyses, non-parametric analysis, data mining analyses (association rules, neural networks, generalized additive models, classification and regression trees, predictive models, CHAD models, cluste analyses, data reduction, classification models), supervised and unsupervised models, time series models, structural equation models, medical informatics, bioinformatics, and fraud detection models.

5. The method according to claim 4, further comprising selecting at least one of the plurality of pre-established statistical analysis types.

6. The method according to claim 2, wherein the data further comprises at least one of numerals and parameters.

7. The method according to claim 6, wherein the data comprises quantitative data.

8. The method according to claim 6, wherein the data comprises business data.

9. The method according to claim 2, further comprising organizing the data to permit the data to be analyzed in accordance with the at least one of a plurality of pre-established statistical analysis types, thereby providing organized data.

10. The method according to claim 9, further comprising processing the organized data according to the at least one of a plurality of statistical analysis types.

11. The method according to claim 2, wherein the processing is performed by a statistical analysis tool for providing processed data.

12. The method according to claim 3, wherein the at least one pre-established rule further comprises merging at least a portion of the pre-established plain language descriptive text with the pre-determined natural language text.

13. The method according to claim 2, wherein the natural language textual output may further comprise at least one graphic display.

14. The method according to claim 13, wherein the at least one graphic display is selected from the group consisting of a table, a chart, and a graph.