Semantic Evaluator for Natural Language Data Modification
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Solution Overview
Problem
Conventional information retrieval systems require precise search terms and Boolean logic, limiting user input to natural language phrases and preventing users from modifying or adding information to stored data, as they lack functionality for interactive modification and extension of search results.
Innovation Solution
A system that processes user input by evaluating semantic structures, identifying expression types, and generating responses, allowing users to input natural language phrases, questions, or commands, and enabling storage, retrieval, and modification of data through a media gateway-based interaction environment with a semantic evaluator and response generating component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional information retrieval systems require precise search terms and Boolean logic, then search precision is improved, but ease of operation deteriorates
Solution Approach 1:
The patent introduces a semantic evaluator as an intermediary component that translates natural language user input into structured query formats. The semantic evaluator analyzes the semantic structure of user expressions, identifies expression types (questions, commands, statements), and converts them into appropriate database queries, thereby mediating between the user's natural language and the system's precise search requirements
Solution Approach 2:
The system changes the parameter of input format acceptance from requiring precise Boolean logic to accepting natural language phrases. By implementing semantic evaluation that processes linguistic patterns and word order, the system transforms the input parameter from structured query syntax to unstructured natural language, improving ease of operation while maintaining search precision through semantic analysis
2Device complexity
If information retrieval systems are limited to retrieval of previously stored information, then system complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The patent implements a multi-functional information retrieval system that not only retrieves stored information but also allows users to add new information, modify existing information, and interact through natural language. The system universally handles multiple expression types (questions, commands, statements) and performs multiple operations (retrieval, addition, modification) within a single integrated environment, eliminating the need for separate systems for different operations
3Reliability
If users cannot modify or add information to stored data, then data integrity is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where the system responds to user expressions with appropriate actions. When users provide commands to add or modify information, the system processes these commands through semantic evaluation, executes the appropriate database operations, and provides feedback responses to confirm the actions taken. This feedback loop allows users to interactively modify data while maintaining system control and data integrity through structured processing
Data Source
AI summary
A method for processing user input includes the step of receiving, during a session, via one of a plurality of media gateways, from a user, an expression having a semantic structure. The semantic structure of the expression is evaluated. An expression type is identified, responsive to the evaluation of the semantic structure. Based on the expression type, a response to the expression is generated. A determination is made as to whether to store the received expression, the response, and an identification of the user.