Document Segment Correlation for Copy Paste Recommendations
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Solution Overview
Problem
Manual selection of content for copying or pasting between documents is time-consuming and not intelligent, lacking efficiency and convenience.
Innovation Solution
A method and system that recommend source or target segments for copying or pasting based on correlation degrees determined through context and metadata analysis, allowing for automated selection of relevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual selection of content for copying or pasting is performed, then user control over the process is maintained, but time consumption increases and efficiency decreases
Solution Approach 1:
The system performs self-service by automatically analyzing context and metadata to determine correlation degrees between source and target segments, eliminating the need for manual content selection while maintaining user control through recommendation-based interaction
Solution Approach 2:
The system performs preliminary action by pre-calculating correlation degrees between potential source segments and target segments based on context and metadata, so that when a user initiates a copy or paste operation, the relevant content is already identified and ready for selection
2Productivity
If automated recommendation system is implemented, then content selection efficiency improves, but system complexity increases
Solution Approach 1:
The system segments the content into discrete segments with associated metadata and context information, allowing the complex correlation analysis to be broken down into manageable comparisons between individual segments based on their metadata characteristics and contextual relationships
Solution Approach 2:
The system introduces an intermediary layer of correlation degree calculation that mediates between the raw content segments and the user's copy/paste operations, translating complex content relationships into a simplified ranking system that guides user selection without exposing the underlying complexity
3Ease of operation
If correlation degree analysis is performed, then intelligence of content selection improves, but processing time increases
Solution Approach 1:
The system performs preliminary action by pre-extracting and storing metadata and context information for all content segments before the user initiates a copy or paste operation, so that correlation degree calculations can be performed quickly using pre-prepared data rather than analyzing raw content in real-time
Solution Approach 2:
The system replaces mechanical manual selection with an automated correlation analysis mechanism that uses metadata and context information to calculate similarity scores, substituting human cognitive processing with computational analysis that is both intelligent and efficient
Data Source
AI summary
A method, system and computer program product for user interface action recommendations. According to the method, a target segment in a target document is determined. Correlation degree between the target segment and at least one source segment in at least one source document is determined. At least one recommended source segment is provided from the at least one source segment based on the correlation degree for a user interface action, such as copying for pasting the target segment.