AI-Driven Data Parsing for Unstructured Sources
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Customized coding solutions for accessing unstructured and semi-structured data are time-consuming, expensive, and inflexible, requiring specialized expertise and being designed for specific data sources, making them ineffective for handling data mapping and transformation processes outside their designed constraints.
Innovation Solution
The development of an AI-driven Generic Data Parsing (GDP) application that automatically parses unstructured and semi-structured data sources, generates normalized and structured data schemas, and loads data into relational formats, accessible via end-user tools, without the need for coding or extensive user expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If customized coding solutions are developed for each data source, then data transformation accuracy is improved, but development time and cost increase significantly
Solution Approach 1:
The patent implements a universal data parsing platform that can handle multiple unstructured and semi-structured data formats (XML, JSON, CSV, COBOL, etc.) through a single system. The platform uses configurable parsing rules and AI-driven interface generation to adapt to different data sources without requiring custom coding for each format, thus resolving the contradiction between transformation accuracy and development time.
Solution Approach 2:
The system enables end-users to independently configure and execute data parsing operations through automatically generated user interfaces. The AI-driven interface generator creates customized UI elements based on the specific data source characteristics, allowing users to perform data transformations without programmer intervention, thereby reducing development time while maintaining accuracy.
2Manufacturing precision
If customized coding solutions are developed for each data source, then data transformation accuracy is improved, but expertise requirements and operational complexity increase
Solution Approach 1:
The system empowers end-users to independently configure parsing operations through AI-generated interfaces that adapt to their specific data sources. Users can select data sources, configure parsing parameters, and execute transformations without requiring programming expertise, thus resolving the contradiction between transformation accuracy and ease of operation.
Solution Approach 2:
The patent introduces an AI-driven interface generator as an intermediary between the user and the complex parsing system. This intermediary automatically generates appropriate UI elements and configuration options based on the data source characteristics, shielding users from technical complexity while maintaining accurate data transformation capabilities.
3Productivity
If customized coding solutions are developed for specific data sources, then parsing effectiveness for that source is improved, but adaptability to other data sources deteriorates
Solution Approach 1:
The patent implements a universal parsing platform that maintains high effectiveness across multiple data sources through configurable parsing rules and AI-driven adaptation. The system can automatically generate appropriate parsing configurations for different data formats (XML, JSON, CSV, COBOL, etc.) while maintaining consistent high-quality transformation results, resolving the contradiction between parsing effectiveness and adaptability.
Solution Approach 2:
The system dynamically adapts its parsing approach based on the specific data source being processed. The AI-driven interface generator and configurable rules engine allow the system to optimize its behavior for each data source while remaining part of a unified platform, thus maintaining both high effectiveness and broad adaptability.
4Ease of operation
If standardized data access tools are used, then ease of operation is improved, but compatibility with unstructured data sources deteriorates
Solution Approach 1:
The patent extends standardized data access tools to handle unstructured and semi-structured data formats through a universal parsing platform. The system maintains the ease of use of standardized tools while adding the capability to process diverse data formats through AI-driven interface generation and configurable parsing rules, resolving the contradiction between ease of operation and data format compatibility.
Data Source
AI summary
Systems and methods for Artificial Intelligence (AI)-driven computer system utilities for generating dynamic User-Interface (UI) elements and loading parsed semi-structured data into a structured data schema, which may then be readily queried utilizing known end-user tools.