Document Classification Using Base Templates
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Solution Overview
Problem
Users face difficulties in classifying and comparing large volumes of similar documents stored in online document stores, such as ADOBE Document Cloud, due to the manual nature of the process, which becomes inefficient as the volume of documents increases.
Innovation Solution
A method and apparatus that utilize base templates to classify and compare documents by extracting metadata, matching it to existing templates, and storing similar documents together, while generating new templates for unmatched documents, allowing for efficient organization and comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual classification and comparison methods are used, then users can organize documents into folders, but the process becomes difficult and inefficient as document volume increases
Solution Approach 1:
The system performs automatic document classification and comparison without requiring user intervention. The computer extracts metadata from documents, matches them to base templates, and organizes similar documents together automatically, allowing the system to serve itself rather than requiring manual user classification.
Solution Approach 2:
The patent replaces the manual mechanical process of document classification with an automated computational system. The computer uses metadata extraction and template matching algorithms to perform classification tasks that would otherwise require manual human effort, substituting mechanical automation for human manual operations.
2Ease of operation
If documents are stored in detailed folder hierarchies for organization, then documents can be categorized, but it becomes difficult to compare and classify particular documents
Solution Approach 1:
The system extracts metadata from documents and separates it from the full document content. This extracted metadata is then used for classification and comparison purposes, allowing the system to analyze document characteristics without requiring users to manually examine entire documents or navigate complex folder structures.
Solution Approach 2:
The base template system serves multiple functions: it classifies documents into categories, enables comparison between similar documents, and organizes storage. A single template structure is used universally across different document types, allowing the same mechanism to handle various classification and comparison tasks.
3Measurement precision
If users manually compare each document to classify it, then accurate classification can be achieved, but the process becomes inefficient with large document volumes
Solution Approach 1:
The system performs preliminary classification by extracting metadata and matching it to base templates before full document analysis is required. This preliminary action using metadata provides accurate classification without requiring manual review of entire documents, maintaining precision while improving processing speed.
Solution Approach 2:
The system uses only the necessary portion of document information (metadata) for classification rather than analyzing entire documents. This partial action approach provides sufficient classification accuracy without the excessive time investment required for complete document review, achieving the right balance between precision and productivity.
Data Source
AI summary
A computer implemented method and apparatus for classifying and comparing similar documents using base templates. The method comprises accessing a document; extracting metadata from the document; matching the metadata to at least one base template of a plurality of base templates; and storing the document with one or more similar documents, wherein the one or more similar documents are documents that match the at least one base template.