Information Representation Structure Analysis for Atypical Document Extraction
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Solution Overview
Problem
Existing document analysis systems fail to efficiently extract target information from atypical documents, as they do not utilize non-textual information such as control characters, spaces, tabs, and external metadata, limiting their ability to interpret document structure accurately.
Innovation Solution
An information representation structure analysis device that identifies information representation grammar and support information types, using templates to generate patterns for extracting target information from atypical documents, incorporating textual and structural data like tables, spaces, and external metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If only text and two-dimensional arrangement information are used for document layout recognition, then the system is simple to implement, but it cannot efficiently extract target information from atypical documents
Solution Approach 1:
The patent segments the document information into multiple types: text information, two-dimensional arrangement information, control character information (tables, spaces, tabs, HTML tags), and external information (headers, footers, invisible document information). This segmentation allows the system to process and utilize diverse information types independently, improving adaptability to atypical documents while managing complexity through modular processing of each information segment.
Solution Approach 2:
The patent creates a universal document analysis system that can handle multiple types of information (text, layout, control characters, external metadata) through a unified approach. The system uses information representation grammar that can accommodate various document formats and structures, making it versatile for different document types while maintaining a consistent processing framework.
2Measurement precision
If multiple types of information (control characters, external metadata, invisible information) are utilized, then extraction accuracy from atypical documents improves, but information processing complexity increases
Solution Approach 1:
The patent introduces information representation grammar as an intermediary layer between the raw document information and the extraction process. This grammar serves as a mediator that standardizes and structures diverse information types (text, control characters, external metadata), making them easier to process while improving extraction accuracy. The grammar acts as a bridge that manages complexity by providing a unified representation framework.
Solution Approach 2:
The patent changes the parameters of information representation by introducing structured grammar rules that define how different information types relate to each other. By transforming raw, unstructured document information into grammar-based representations with defined relationships and hierarchies, the system improves extraction accuracy while managing complexity through parameterized information structures.
Data Source
AI summary
An information representation structure analysis device: stores an information representation template for each combination of an information representation grammar and a support information type, the information representation template being a template used to generate an information representation pattern being a program code for implementing a function of extracting an extraction target, the support information type being a category of support information being information used in extraction of the extraction target; identifies the information representation template to be used to generate the information representation pattern for extraction of the extraction target from an atypycal document, based on the information representation grammar and the support information type identified for the information representation; and generates the information representation pattern by applying the extraction target and basis information to the identified information representation template, the basis information being a basis in extraction of the extraction target from the information representation.