Automated Term Extraction for Test Script Functional Diagrams
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Solution Overview
Problem
Manual generation of functional diagrams for test script documents is time-consuming, prone to errors, and requires significant computational resources, especially when dealing with large numbers of test scripts.
Innovation Solution
A cloud platform that employs term extraction techniques, including skip n-gram analysis, to automatically identify significant terms and relationships, reducing the time and resources needed to generate functional diagrams by processing test script documents and forming hierarchies among extracted terms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual generation of functional diagrams is used for test script documents, then accuracy and understanding can be maintained through human review, but the process becomes time-consuming and requires significant computational resources
Solution Approach 1:
The system performs self-service by automatically extracting terms and generating functional diagrams without requiring manual human intervention. The automated term extraction system processes test script documents independently, identifying significant terms and generating diagrams autonomously, thereby eliminating the time-consuming manual generation process while maintaining accuracy through systematic analysis
2Measurement precision
If manual generation of functional diagrams is used, then detailed analysis can be performed, but significant computational resources are required
Solution Approach 1:
The system extracts only the essential and significant terms from test script documents using automated term extraction techniques. By identifying and extracting key terms rather than processing entire documents manually, the system performs detailed analysis on condensed data, reducing computational resource requirements while maintaining the quality of detailed analysis through focused processing of extracted terms
3Productivity
If automated term extraction is implemented, then time and computational resources are reduced, but the complexity of the extraction process increases
Solution Approach 1:
The automated term extraction process is segmented into distinct sequential steps: obtaining test script documents, identifying significant terms using skip n-gram analysis, extracting terms based on predefined criteria, and generating functional diagrams from extracted terms. This segmentation of the complex extraction process into manageable stages reduces overall process complexity while maintaining high productivity through systematic automated processing
Data Source
AI summary
A device may obtain a document. The device may identify a skip value for the document. The skip value may relate to a quantity of words or a quantity of characters that are to be skipped in an n-gram. The device may determine one or more skip n-grams using the skip value for the document. A skip n-gram, of the one or more skip n-grams, may include a sequence of one or more words or one or more characters with a set of occurrences in the document. The sequence of one or more words or one or more characters may include a skip value quantity of words or characters within the sequence. The device may extract one or more terms from the document based on the one or more skip n-grams. The device may provide information identifying the one or more terms.