Strategy Tree Module for Data Mining Visualization
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Solution Overview
Problem
Existing data mining systems face limitations in efficiently integrating data mining outputs with user-defined metrics and rules, requiring extensive manual efforts and being prone to errors, especially in deploying data mining models and strategies, and lack effective visualization for multidimensional data sources.
Innovation Solution
A method involving a strategy tree module that allows users to define, deploy, and verify business strategies through a graphical user interface, using conditional, calculation, and treatment expressions to split datasets, generate calculated values, and apply treatments, enabling efficient integration and visualization of data mining outputs within a unified environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If decision trees are used for data mining analysis, then relationships and patterns can be revealed, but the amount of time required to create decision tables is extensive
Solution Approach 1:
The patent segments the data mining process into distinct components: automated tree generation, visual editing interface, and deployment modules. This allows users to work with pre-generated tree structures rather than creating decision tables from scratch, significantly reducing time while maintaining analytical capability.
Solution Approach 2:
The system performs preliminary actions by automatically generating decision trees and decision tables before user interaction. The visual editor then allows users to modify these pre-generated structures, eliminating the time-consuming manual creation process while preserving the ability to perform detailed analysis.
2Reliability
If data mining models and strategies are deployed using traditional methods, then the models can be implemented, but the process involves time consuming manual programming steps
Solution Approach 1:
The patent replaces manual programming mechanics with automated code generation. The visual editor allows users to configure deployment parameters through graphical interfaces, and the system automatically generates the necessary programming code, eliminating time-consuming manual coding while ensuring reliable model deployment.
Solution Approach 2:
The deployment system performs self-service by automatically generating deployment code and configurations based on user specifications in the visual editor. This eliminates the need for manual programming intervention while maintaining deployment reliability through automated code generation and validation.
3Reliability
If segments are integrated with cost, profit, and business drivers, then business strategies can be validated, but the process is time consuming and error prone
Solution Approach 1:
The patent implements feedback mechanisms that automatically calculate and display business metrics (cost, profit, KPIs) when segments are created or modified in the visual editor. This real-time feedback eliminates manual validation steps, reducing time and errors while maintaining accurate strategy validation through automated metric computation and comparison.
4Adaptability or versatility
If a unified visual environment is used for data mining operations, then integration of scores with user defined metrics is improved, but the system complexity increases
Solution Approach 1:
The patent implements a universal visual editor that handles multiple data mining operations (segmentation, scoring, metric integration, strategy validation) through a single interface. This multi-functional approach improves adaptability and integration capability while managing system complexity by providing a unified, consistent user experience across different operations rather than requiring separate specialized tools.
Data Source
AI summary
A method for applying a strategy to a dataset in a data mining system to address a business problem, comprising: receiving at least one conditional expression defining the strategy from a user through a graphical user interface (“GUI”) displayed on a display screen of the data mining system; applying the conditional expression to the dataset to split the dataset into segments; displaying the segments as nodes in a tree structure on the display screen; receiving a calculation expression for operating on one or more values in one or more of the segments; applying the calculation expression to one or more of the segments to generate one or more respective calculated values; displaying the one or more calculated values in respective nodes of the tree structure; receiving a treatment expression for operating on the calculated values; applying the treatment expression to one or more of the calculated values to generate respective responses to the business problem; and, displaying the responses in respective nodes of the tree structure to thereby address the business problem.