Merging Supplemental Notes with Source Documents via Machine Learning
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Solution Overview
Problem
In group settings where multiple individuals are evaluating the content of an electronic document, the process of modifying the document is impacted by limitations on simultaneous editing, leading to data corruption and bottlenecks.
Innovation Solution
A computer-implemented method that receives copies of notes from participants, identifies note fragments, and uses machine learning models to compare and merge these fragments with the source document, creating a pseudo-source document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple users are allowed to edit the same electronic document simultaneously, then collaboration efficiency is improved, but data corruption risk increases
Solution Approach 1:
The patent segments the document editing process by allowing users to work on different portions or versions of the document simultaneously. The system divides the document into manageable sections that can be edited independently, then integrates these segments through automated merging processes, thus enabling concurrent editing while maintaining data integrity.
Solution Approach 2:
The patent introduces an intermediary merging system that acts as a mediator between multiple users editing the same document. This intermediary component automatically reconciles conflicting edits, manages version control, and integrates changes from different users, allowing simultaneous editing without direct conflicts that would cause data corruption.
2Reliability
If only one user can edit the document at a time, then data corruption is avoided, but collaboration productivity decreases
Solution Approach 1:
The patent implements dynamic editing permissions and document states that adapt based on user actions and document conditions. Rather than static single-user or multi-user modes, the system dynamically adjusts editing capabilities, allowing transitions between different collaboration states while maintaining data integrity through automated conflict resolution mechanisms.
Solution Approach 2:
The patent ensures continuous productive collaboration by implementing automated background processes that continuously merge, reconcile, and integrate changes from multiple users. This continuous automated action eliminates idle waiting time between sequential edits, maintaining uninterrupted productivity while preserving data integrity through systematic integration processes.
3Manufacturing precision
If manual merging of notes is performed, then document accuracy is maintained, but time consumption increases
Solution Approach 1:
The patent implements self-service automated merging capabilities that perform document integration without requiring manual human intervention. The system automatically detects changes, reconciles conflicts, and merges notes from multiple sources while maintaining accuracy through built-in validation and verification processes, eliminating time-consuming manual merging operations.
Solution Approach 2:
The patent replaces manual mechanical merging processes with automated computational systems. Instead of human operators manually comparing and integrating document changes, the system uses automated algorithms and software agents to perform the merging operation, significantly reducing time consumption while maintaining or improving accuracy through systematic conflict resolution.
Data Source
AI summary
A computer-implemented method, according to one embodiment, includes: receiving copies of notes that were originally recorded by participants, the notes corresponding to a source document. Note fragments in the received copies of notes are identified and one or more machine learning models are used to compare the identified note fragments to pages and paragraphs in the source document that the respective note fragments are located in. Based at least in part on the comparison, the identified note fragments are merged with a copy of the source document to form a pseudo-source document. Furthermore, the pseudo-source document is output.