NLP Text Block Scoring for Dynamic Document Conciseness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional documents often contain information irrelevant to specific audiences, leading to delays and incorrect interpretations due to their broad targeting, which can be addressed by increasing document conciseness.
Innovation Solution
A system utilizing natural language processing to generate text block scores, hiding irrelevant text blocks, and providing a modified document with indicators, allowing users to focus on relevant information through user-specific criteria and summarization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a document is written to address multiple target audiences, then the document can serve broader needs, but the document incorporates irrelevant information that increases response time and reduces interpretation accuracy
Solution Approach 1:
The patent segments the document into multiple text blocks with different relevance scores, allowing the system to present only the most relevant portions to specific user demographics. This segmentation enables the document to serve multiple audiences efficiently by hiding irrelevant text blocks from each user type, thus reducing their response time while maintaining broad adaptability.
Solution Approach 2:
The patent implements dynamic document presentation where text blocks are shown or hidden based on real-time user characteristics and relevance scores. The system dynamically adjusts the document content displayed to each user, transforming a static multi-audience document into an adaptive presentation that reduces irrelevant information for each specific user, thereby decreasing response time.
2Adaptability or versatility
If a document is written to address multiple target audiences, then the document can serve broader needs, but the document incorporates irrelevant information that reduces interpretation accuracy
Solution Approach 1:
By segmenting the document into scored text blocks, the system can filter and present only the most relevant information to each user demographic. This segmentation improves interpretation accuracy by eliminating irrelevant information from the user's view, while the underlying segmented structure maintains the document's ability to serve multiple audiences.
Solution Approach 2:
The patent extracts and removes irrelevant text blocks from the user's view based on relevance scoring, while retaining them in the full document for other audiences. This extraction process improves interpretation accuracy for each specific user by presenting only pertinent information, while the document maintains its multi-audience adaptability through selective presentation.
3Productivity
If natural language processing is used to generate text block scores and hide irrelevant blocks, then document conciseness is increased and response time is reduced, but the system complexity increases
Solution Approach 1:
The system implements self-service through automated natural language processing that automatically scores and hides irrelevant text blocks without requiring manual intervention. This automation increases productivity by efficiently processing documents and reducing response time, while the self-optimizing nature of the system manages its own complexity through automated relevance assessment.
Solution Approach 2:
The patent changes the parameter of text block visibility based on dynamically calculated relevance scores. By adjusting this single parameter (visibility) based on NLP-generated scores, the system achieves high productivity in presenting relevant information while managing complexity through a straightforward parameter-based filtering mechanism rather than complex structural changes.
Data Source
AI summary
A method may include obtaining a document and using a first prediction model to generate text block scores for text blocks in the document, where a first text block of the text blocks is associated with a first text block score of the plurality of text block scores. The method also includes updating, in response to the first text block score for the first text block failing to satisfy a criterion, a modified version of the document with an indicator to set the first text block as a hidden text block in a presentation of the modified version. The method also includes generating a summarization of the first text block based on the words in the first text block and updating the modified version of the document to include the summarization. The method also includes providing the modified version of the document to a user device.