Automated Data Analysis System for Natural Language Insight Generation
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Solution Overview
Problem
Existing data analysis methods, such as statistical modeling, are often difficult to interpret for non-specialists and require laborious exploration with preconceived hypotheses, limiting their effectiveness in uncovering patterns in customer data.
Innovation Solution
A method and system that analyze data records by selecting a variable of interest, determining correlations with other variables, and generating natural language descriptions of these correlations, using a computer to automate the process and present findings in a ranked list of 'insight snippets' that highlight predictive power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical models are used to analyze data, then analytical depth is improved, but interpretability deteriorates for non-specialist users
Solution Approach 1:
The patent introduces an intermediary system that translates statistical model outputs into natural language descriptions. The system uses template-based generation to convert complex analytical results into human-readable formats, acting as a mediator between the statistical model and non-specialist users.
Solution Approach 2:
The system changes the parameter of information representation from technical statistical formats to natural language. By transforming the output format while preserving the underlying analytical depth, the system makes results accessible to non-specialists without sacrificing analytical rigor.
2Loss of information
If manual exploration with hypotheses is used, then understanding of data patterns is improved, but time consumption deteriorates
Solution Approach 1:
The system enables self-service data analysis by automatically generating insights without requiring manual hypothesis exploration. The automated natural language generation system performs the analytical work independently, eliminating the need for users to manually explore data with preconceived hypotheses.
Solution Approach 2:
The system performs preliminary analytical actions by automatically generating hypotheses and insights before the user needs them. Rather than waiting for users to formulate and test hypotheses manually, the system proactively generates data pattern understanding in advance.
3Productivity
If automated analysis is implemented, then productivity is improved, but complexity of the system deteriorates
Solution Approach 1:
The patent segments the automated analysis system into distinct functional modules: data processing components, statistical analysis components, and natural language generation components. This modular segmentation manages system complexity by dividing the automated analysis function into manageable, independent units.
Solution Approach 2:
The system employs universal template structures that can handle multiple types of statistical results and data patterns. By using multi-functional templates that adapt to different analysis outcomes, the system achieves high productivity without proportionally increasing complexity.
Data Source
AI summary
A computer implemented method and system for analyzing a set of data records is provided. Each data record comprises a value for each of a plurality of variables and the method comprises receiving a selection of a variable of interest from the plurality of variables; analyzing values in the data records of at least one variable of the plurality of variables other than the variable of interest; and using the analysis to create a statistical description of said at least one variable. The statistical description is then used to populate at least one template natural language description of a relationship between the variable of interest, or a value or range of values of the variable of interest, and the variable to which the statistical description applies.