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A natural language user interface for fuzzy scope queries.

Yan Huang1, Hong-Feng Yu, Wei-Dong Geng

  • 1College of Computer Science and Engineering, Zhejiang University, Hangzhou 310027, China.

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Summary
This summary is machine-generated.

This study introduces a two-agent system for natural language queries in information systems. It converts English sentences into precise SQL statements, improving data retrieval accuracy.

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Area of Science:

  • Computer Science
  • Information Retrieval
  • Natural Language Processing

Background:

  • Information systems often lack intuitive query interfaces.
  • Natural language processing (NLP) offers potential for user-friendly data access.
  • Handling ambiguity in user queries is a significant challenge.

Purpose of the Study:

  • To develop a two-agent framework for natural language querying of information systems.
  • To enable users to pose scope queries using single English sentences.
  • To effectively handle and resolve vague or imprecise query requirements.

Main Methods:

  • A parsing agent interprets natural language sentences, generating a fuzzy Structured Query Language (SQL) statement.
  • A defuzzifying agent refines the fuzzy SQL into an executable precise SQL statement using fuzzy logic rules.
  • The parsing agent interactively queries users to disambiguate requirements.

Main Results:

  • A prototype interface demonstrating the framework's effectiveness was successfully implemented.
  • The system accurately translates natural language scope queries into executable SQL.
  • Adaptive defuzzification strategies were detailed and validated.

Conclusions:

  • The proposed two-agent framework provides an effective solution for natural language querying.
  • The system enhances user interaction by resolving query ambiguity through adaptive defuzzification.
  • This approach improves the accessibility and usability of information systems.