Content Prediction via Regular Expression Pattern Analysis
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Solution Overview
Problem
Current data processing systems are limited in their ability to predict complex patterns, requiring users to expend significant time and effort for data management, and custom scripts or macros, which are not easily shareable or adaptable across users.
Innovation Solution
A computer-implemented method using regular expression pattern analysis to compare differences between sample and target sets of cells, allowing users to configure and preview content predictions, and embed prediction logic within documents for standardized data formatting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple content prediction logic is used, then ease of operation is improved, but prediction capability for complex patterns deteriorates
Solution Approach 1:
The system changes the parameter of pattern recognition from simple to complex by introducing regular expression analysis. This allows the content prediction to handle complex patterns while maintaining ease of use through automated pattern detection without requiring users to manually create complex prediction logic.
Solution Approach 2:
The system performs self-service by automatically detecting and analyzing patterns in the data using regular expression analysis. Instead of requiring users to manually create complex prediction rules, the system autonomously identifies patterns and generates appropriate prediction logic, thereby maintaining ease of operation while improving prediction capability.
2Adaptability or versatility
If custom scripts and macros are created to handle complex data formatting, then prediction capability for complex patterns is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The system eliminates the need for users to create custom scripts by performing pattern analysis automatically. The regular expression analysis is executed autonomously by the system, detecting patterns in sample data and generating prediction rules without user intervention in the scripting process, thereby reducing device complexity while maintaining high prediction capability.
Solution Approach 2:
The system introduces regular expression analysis as an intermediary mechanism between raw data and prediction output. This intermediary layer automatically translates complex data patterns into actionable prediction rules, eliminating the need for users to directly create and manage complex custom scripts or macros.
3Adaptability or versatility
If custom scripts are created for data formatting, then prediction capability is improved, but loss of time increases due to creation and maintenance effort
Solution Approach 1:
The system performs preliminary pattern analysis on sample data to automatically generate prediction rules before the user needs to apply them. By pre-processing the data to identify patterns and create the necessary prediction logic in advance, the system eliminates the time-consuming task of manually creating and maintaining custom scripts for each new data formatting requirement.
Solution Approach 2:
The system handles the time-consuming pattern analysis and script generation autonomously. Instead of requiring users to spend time creating, testing, and maintaining custom scripts, the system self-services by automatically detecting patterns in sample data and generating the necessary prediction rules, thereby significantly reducing the time loss associated with script creation and maintenance.
4Ease of operation
If simple content prediction is used, then ease of operation is improved, but data management efficiency deteriorates
Solution Approach 1:
The system enhances data management efficiency by changing the prediction parameter from simple to complex pattern recognition using regular expressions. This allows the system to automatically handle complex data formatting requirements while maintaining ease of operation through automated pattern detection, thereby improving productivity without sacrificing user-friendliness.
Data Source
AI summary
A computer implemented method, apparatus, and computer usable program code for content prediction. Differences between a sample set of cells and a target set of cells are compared to identify a pattern based on regular expression analysis. A preview of content prediction changes is presented for a user selection. Content predictions changes are made to the user selection in response to receiving a preview acceptance accepting the preview.