Dynamic Recommendation System for Correlated Metrics
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Solution Overview
Problem
Interpreting correlations between artificial intelligence metrics and key performance indicators is challenging due to the complexity of correlation coefficients, which are often difficult for non-experts to understand, hindering effective decision-making in organizational processes.
Innovation Solution
A computer system generates human-readable recommendations by determining key performance values and metric values from data, identifying significant correlations using correlation coefficients, and presenting actionable insights through recommendation patterns, allowing users to understand and act on these correlations without requiring statistical expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If correlation coefficients are used to measure relationships between metrics and KPIs, then measurement precision is improved, but ease of operation deteriorates because non-experts find correlation coefficients difficult to understand
Solution Approach 1:
The patent introduces natural language recommendations as an intermediary between the statistical correlation coefficients and the end users. The system generates human-readable recommendations that explain the practical implications of correlations without requiring users to understand statistical concepts, thus maintaining measurement precision while improving ease of operation
Solution Approach 2:
The patent creates simplified copies of the complex correlation data in the form of natural language recommendations. Instead of presenting raw correlation coefficients, the system generates readable statements that capture the essential meaning of the statistical relationships in an accessible format
Data Source
AI summary
A method, apparatus, system, and computer program product for generating a human readable recommendation. The method determines, by a computer system, a key performance value for a key performance indicator from a collection of data; A metric value for a metric is determined by the computer system from the collection of data. A correlation coefficient indicating a correlation between the key performance indicator and the metric is identified by the computer system. A human readable recommendation is generated by the computer system using a recommendation pattern when the correlation coefficient indicates that the correlation between the key performance indicator and the metric is sufficiently significant.