Embedded Document Metadata for Accurate Automated Parsing
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Solution Overview
Problem
Existing electronic document formats, such as DOCX and PDF, store information in an unstructured manner, making it difficult for automated parsing software to accurately interpret and extract relevant data, leading to misread or miscategorized information, which can prevent resumes or documents from reaching human reviewers or result in incorrect information being viewed.
Innovation Solution
Encoding document content according to a defined schema and embedding it as non-visible metadata in the document, optionally encrypting it, allows for accurate parsing by an enhanced document parsing system that can decode and extract the structured data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If documents are stored in visually appealing formats like DOCX or PDF, then human readability is improved, but automated parsing accuracy deteriorates due to unstructured information storage
Solution Approach 1:
The document is segmented into two distinct layers: a visual presentation layer (DOCX/PDF) for human readability and a structured data layer (XML/JSON metadata) for machine parsing. The encoding system divides the document content into structured elements that can be independently processed, allowing parsers to access organized data while humans view the formatted document.
Solution Approach 2:
An intermediary encoding system acts as a mediator between the visual document format and the parsing system. This intermediary layer encodes the document content according to a defined schema and embeds it as structured metadata, enabling accurate extraction by parsers without compromising the visual presentation for human readers.
2Measurement precision
If structured data formats like XML or JSON are used, then machine readability is improved, but visual presentation capability deteriorates
Solution Approach 1:
The system merges two previously separate document formats into a single enhanced document. The structured data (XML/JSON) and visual presentation (DOCX/PDF) are combined into one file with embedded metadata, allowing both machine readability and visual presentation capability to coexist in the same document.
Solution Approach 2:
The structured data layer is nested within the visual document structure. The XML or JSON schema-encoded content is embedded as metadata within the DOCX or PDF file format, creating a nested structure where the structured data resides inside the visual presentation container, enabling both functions simultaneously.
3Measurement precision
If document content is embedded as metadata, then parsing accuracy is improved, but device complexity increases due to encoding and decryption requirements
Solution Approach 1:
The document encoding and schema registration are performed in advance during document creation. The content is pre-encoded according to the defined schema and embedded as metadata before the parsing stage, eliminating the need for complex real-time encoding operations during parsing and reducing system complexity at the processing stage.
Data Source
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AI summary
The disclosed enhanced document creation and parsing systems deal with enhanced documents that allow for the presentation of document content in a preferred visual manner, while ensuring that the document content can be captured accurately by an automated parser with nothing being discarded or misrepresented. The enhanced document creation system may create an enhanced document by encoding document content in accordance with a defined schema, optionally encrypting the resulting structured data into an encrypted byte string, and embedding the encrypted byte string as non-visible metadata in a rendered document. The resulting enhanced document can be completely and accurately parsed by an enhanced document parsing system that is capable of extracting, decrypting and decoding the embedded document metadata.