Regulatory Tree Parser for Hierarchical Text Segmentation
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Solution Overview
Problem
Traditional regulatory parsers fail to efficiently process and parse regulatory documents, losing hierarchical structure and relationships between text segments, leading to incomplete text retrieval and increased search times due to varying document formats and lack of granular text storage.
Innovation Solution
A regulatory tree parser that partitions text into segments based on formatting features, organizes them into a structured tree with a hierarchy, and stores them in a single format, maintaining relationships between text segments and documents, allowing efficient querying and manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional regulatory parsers process documents at document level or arbitrary granularity, then processing speed is maintained, but text completeness and hierarchical structure are lost
Solution Approach 1:
The patent divides regulatory documents into hierarchical segments (sections, subsections, paragraphs, sentences) and represents them as nodes in a tree structure. Each node contains text content and metadata about its position and relationships, enabling both fine-grained text retrieval and efficient processing by only loading relevant segments.
Solution Approach 2:
The patent implements a nested tree structure where sections contain subsections, which contain paragraphs, which contain sentences. This hierarchical nesting allows the system to maintain complete textual information while enabling efficient querying at any level of granularity without processing the entire document.
2Loss of time
If traditional parsers store text without hierarchical structure, then storage simplicity is maintained, but search time and resource usage increase
Solution Approach 1:
The patent pre-processes regulatory documents during ingestion to build the hierarchical tree structure and create an index. This preliminary organization of text segments into a structured format with metadata about positions and relationships enables fast retrieval operations without requiring complex queries during search operations.
3Adaptability or versatility
If regulatory documents are stored in different formats, then document diversity is maintained, but processing complexity and time increase
Solution Approach 1:
The patent implements a universal tree data structure that can represent text from any document format. The parser accepts multiple input formats (PDF, HTML, plain text) and converts them all into the same standardized hierarchical tree structure, enabling downstream applications to process all documents uniformly regardless of their original format.
Data Source
AI summary
Described herein is a regulatory parser that downloads and efficiently processes regulatory documents. The regulatory documents may be from different sources and may have different formats. The regulatory parser parses all of the text in the regulatory documents and converts into a predetermined, single format for downstream applications. The text is organized and stored in a structured tree, organized into one or more hierarchies with nodes storing segments of text from a regulatory document. In some embodiments, each node in the regulatory tree may represent a segment of text. Partitioning the text of a regulatory document into segments of text may make the storage and querying of the regulatory documents more manageable. The organization and structure of the structured tree may reduce the times and resources needed for accessing and searching for a regulatory citation. The structured tree may allow a user to manipulate a regulatory document or text.