Multilingual Document Field Extraction Using Encoding Threshold Matching
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Solution Overview
Problem
Conventional approaches to extracting information from documents are not specific or robust enough to reliably identify the meaning of text in multiple languages, leading to inaccurate determination of key-value pairs and dependent on large quantities of training documents for each language.
Innovation Solution
A document field identification system that determines key-value pairs by encoding key fields and comparing them to predefined encodings within a threshold distance, allowing for accurate assignment of field types regardless of language, without relying on extensive training data or neural networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional approaches are used to extract information from documents, then text extraction can be performed, but the accuracy of identifying the meaning of extracted text in various languages deteriorates
Solution Approach 1:
The patent introduces an encoding intermediary that converts key fields from different languages into a language-agnostic numeric representation. This encoding acts as a mediator between the extracted text and the field type determination process, enabling accurate matching without being affected by language variations. The encoding compares the extracted key field against a predefined set of encodings to determine the most likely field type.
Solution Approach 2:
The patent transforms the key field from its original textual form into a numeric encoding representation. This parameter change from text to numeric encoding allows for more robust comparison and matching, as numeric encodings can capture semantic meaning while being invariant to language-specific variations in text representation.
2Adaptability or versatility
If conventional approaches are used for multi-language document processing, then text extraction is possible, but the robustness of identifying field meanings across languages deteriorates
Solution Approach 1:
The patent creates a universal encoding system that can represent key fields from any language in a common numeric format. This universal representation enables the same field type determination logic to be applied across all languages, making the system multi-functional without sacrificing precision. The predefined encodings serve as a universal reference set that can match against extracted fields regardless of their source language.
3Productivity
If conventional approaches are used to process documents, then information extraction can be performed, but the accuracy of determining key-value pairs deteriorates
Solution Approach 1:
The patent performs preliminary encoding of the extracted key field before the field type determination step. By pre-computing the encoding and having a predefined set of reference encodings ready, the system can quickly and accurately determine field types without requiring complex post-processing or additional training data analysis, thus maintaining high productivity while improving accuracy.
Data Source
AI summary
A method for multi-language document field extraction may include determining, based on a received document including a plurality of key fields and a plurality of value fields, a plurality of key-value pairs. The method also includes determining whether an encoding of a key field is within a threshold distance from a predetermined encoding of a predefined key field associated with a predefined field type. The method further includes assigning, based on determining the encoding of the key field is within the threshold distance, the predefined field type to the corresponding key-value pair. The method also includes performing a document processing operation based on each key-value pair and the predefined field type assigned to each key-value pair. Related systems and methods are provided.