Document Lineage Management Using ML Section Analysis
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Solution Overview
Problem
Existing document management systems struggle to accurately determine and manage the lineage of documents independently edited by separate devices without relying on metadata, which can be inaccurate or incomplete, leading to inefficiencies and resource wastage.
Innovation Solution
A document management system utilizing a machine learning model and similarity analysis to compare sections of documents, identifying lineages based on characteristics and differences, and filtering out irrelevant sections to efficiently determine document lineage without metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metadata is used to determine document lineage, then the process is simple and fast, but the accuracy is poor when metadata is inaccurate or incomplete
Solution Approach 1:
The system segments the document into multiple sections and analyzes each section independently to determine lineage. By dividing the document into smaller units and comparing corresponding sections across versions, the system achieves more accurate lineage determination while managing computational complexity through focused local analysis rather than global comparison.
Solution Approach 2:
The system introduces an intermediary machine learning model that acts as a mediator between raw document sections and lineage determination. This model processes section characteristics and differences to infer lineage relationships, providing accurate results even when traditional metadata is unavailable or incomplete.
2Reliability
If all document sections are analyzed to determine lineage, then comprehensive lineage information is obtained, but computing resources are wasted on irrelevant sections
Solution Approach 1:
The system extracts and focuses only on the most relevant sections for lineage determination by analyzing section characteristics and differences. By identifying and isolating key sections that contain meaningful changes, the system achieves reliable lineage determination while avoiding unnecessary computation on irrelevant sections.
Solution Approach 2:
The system applies different analysis depths to different sections based on their relevance. Rather than uniformly analyzing all sections, the system concentrates computational resources on sections showing significant changes or containing important lineage information, while using lighter analysis for stable sections.
3Measurement precision
If machine learning models are used to analyze document sections, then accurate lineage is determined without metadata, but the processing time increases
Solution Approach 1:
The system performs preliminary analysis by first identifying sections with significant changes or characteristics before applying the full machine learning model. This preliminary filtering step reduces the number of sections requiring intensive ML analysis, thereby maintaining accuracy while reducing overall processing time.
Solution Approach 2:
The system applies the machine learning model selectively to only those sections where it is most needed - sections showing meaningful changes or where metadata is unavailable. By using partial action rather than exhaustive analysis of all sections, the system achieves accurate lineage determination with reduced processing time.
Data Source
AI summary
In some implementations, a system may obtain document lineage training data associated with a plurality of historical documents and corresponding lineage data of independent historical documents of the plurality of historical documents. The system may train, based on the document lineage training data, a lineage analysis model to determine a lineage of edited sections of a source document. The system may receive a plurality of document files that correspond to a plurality of versions of a document. The system may determine, using a similarity analysis model, that a first section from a first version of the plurality of versions corresponds to a second section from a second version of the plurality of versions. The system may determine, using the lineage analysis model, a lineage of a corresponding section of the document that is associated with the first section and the second section.