Interactive Data Mining System for Non-Expert Insight Extraction
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Solution Overview
Problem
Existing data mining techniques require expert input and guidance, and often produce results that are either obvious or incorrect, making them inaccessible to non-experts and inefficient in extracting meaningful patterns from large data sets.
Innovation Solution
A data mining system that determines correlations between columns of a data set and displays an interactive listing of correlated pairs, allowing users to select values and refine the data set without requiring human input, using methods like Pearson correlation to identify statistical relationships and provide insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data mining techniques are used, then expert input and guidance are required, but this makes the system inaccessible to non-experts and reduces ease of operation
Solution Approach 1:
The patent introduces an automated correlation analysis system that acts as an intermediary between the data set and the user. The system automatically calculates correlations between data columns and presents results in an interactive format, eliminating the need for users to directly perform complex data mining operations or provide expert guidance while still achieving accurate results
2Measurement precision
If traditional data mining techniques are used, then custom code and complex computations are required, but this increases device complexity and reduces ease of manufacture
Solution Approach 1:
The system performs self-service by automatically calculating correlations between all pairs of data columns without requiring external expert intervention or custom code writing. The automated correlation analysis engine independently processes the data set, identifies patterns, and presents results, thereby reducing system complexity while maintaining detection accuracy
3Measurement precision
If traditional data mining techniques are used, then the process requires careful model-building and deep initial insight, but this increases loss of time and reduces productivity
Solution Approach 1:
The system performs preliminary action by automatically calculating all pairwise correlations between data columns at the outset. This preliminary correlation analysis provides immediate insights into data relationships without requiring iterative model-building or deep initial expert insight, thereby reducing the time required to achieve accurate results while maintaining insight quality
Data Source
AI summary
A data mining system receives a data set that includes a plurality of columns of data. The system determines correlations between columns of data of the data set and displays an interactive listing of a plurality of pairs of columns based on the correlations. The listing includes preview information based on the correlations for each pair. The system receives a selection of a value from the interactive listing from a user and refines the data set in response to the selection.