Natural Language Query System for Unstructured Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data analysis processes are inefficient as they require manual database query creation and data organization, making it time-consuming for businesses to derive actionable insights from disparate data sources using natural language processing.
Innovation Solution
A computerized system and process that receives natural language queries, retrieves and structures unstructured data, and generates an interactive reporting interface, allowing users to input keywords and filter results for enhanced data visualization and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data analysis processes are used, then data analysts can generate comprehensive reports from disparate data sources, but the process is time-consuming and inefficient
Solution Approach 1:
The patent replaces manual mechanical data analysis processes with an automated natural language processing system. The system uses NLP to automatically parse unstructured data, extract entities and relationships, generate database queries, and produce reports without manual intervention, thereby dramatically improving productivity and reducing time loss.
Solution Approach 2:
The system enables self-service data analysis by allowing business users to interact with the system through natural language queries. The system automatically processes these queries, retrieves relevant data from multiple sources, and generates reports without requiring users to manually create queries or analyze data, thus eliminating time loss while maintaining comprehensive analysis capabilities.
2Measurement precision
If manual query creation and data organization is performed, then accurate data retrieval from disparate sources is achieved, but the complexity and time required increases
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates user-friendly natural language queries into precise database queries. This intermediary layer maintains data retrieval accuracy by ensuring queries correctly access disparate data sources, while simultaneously reducing process complexity by eliminating the need for users to manually construct complex queries and organize data.
Solution Approach 2:
The system replaces manual query creation and data organization mechanics with automated NLP-based query generation. The system automatically parses natural language input, generates appropriate SQL queries, retrieves data from multiple sources, and organizes results, thereby maintaining precision while dramatically reducing process complexity.
3Loss of information
If static reports are generated manually, then comprehensive business intelligence is provided, but interactivity and user engagement are limited
Solution Approach 1:
The patent transforms static report generation into a dynamic, interactive system. Users can engage with the system through natural language conversations, ask follow-up questions, and explore data from multiple angles. The system dynamically generates and executes queries based on user interactions, maintaining comprehensive business intelligence while dramatically improving ease of operation and user engagement.
Solution Approach 2:
The system implements feedback mechanisms where user interactions with natural language queries are processed and reflected in subsequent report generations. The system learns from user preferences and interaction patterns, adjusting query generation and report presentation to better meet user needs, thereby maintaining information quality while enhancing operational ease through continuous user feedback.
Data Source
AI summary
The present invention is directed to a computerized system and process for natural language query and reporting comprising a processor, memory, and a query interface configured for receipt of a data source selection. The processor searches and retrieves over a network unstructured data based on the received data source selection, parses the unstructured data into data blocks and stores the data blocks in a local database. The processor semantically parses the data blocks and stores the resulting data in a structured database.A report module is configured to iteratively receive keyword input and instantiate a subject node, the node representing a subset of data blocks of the structured database having the input keywords. The report module creates a taxonomy based on the input keywords, with descendant levels representing a subset of data blocks of the subject node, the subset of data blocks having the input keywords combined with other words in the data blocks. The report module further associates a keyword selector with the subject node, the keyword selector presenting an interface for additional user keyword input.