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Related Experiment Videos

Fuzzy query translation for relational database systems.

S M Chen1, W T Jong

  • 1Dept. of Comput. & Inf. Sci., Nat. Chiao Tung Univ., Hsinchu.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|January 1, 1997
PubMed
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This study introduces a novel fuzzy query translation method using fuzzy numbers and alpha-cuts. It enhances database usability for new users by enabling intuitive fuzzy queries and flexible retrieval thresholds.

Area of Science:

  • Database Management
  • Fuzzy Logic Systems
  • Information Retrieval

Background:

  • Traditional relational database systems lack flexibility in handling imprecise or vague user queries.
  • Existing query languages require users to specify exact conditions, posing challenges for non-expert users.
  • Fuzzy logic offers a framework for representing and processing imprecise information.

Purpose of the Study:

  • To develop a user-friendly fuzzy query translation method for relational databases.
  • To enable the representation of retrieval conditions using fuzzy terms (fuzzy numbers).
  • To enhance the flexibility and accessibility of database systems for inexperienced users.

Main Methods:

  • The proposed method utilizes alpha-cuts operations on fuzzy numbers to define fuzzy query conditions.

Related Experiment Videos

  • Fuzzy terms representing user's retrieval intentions are translated into precise SQL queries.
  • A fuzzy query translator tool was implemented to automate this translation process.

    • Main Results:

    • The implemented fuzzy query translator successfully converts user-defined fuzzy queries into executable SQL queries.
    • The method allows for intuitive query construction by users, accommodating vague or imprecise information needs.
    • Users can adjust retrieval threshold values, offering greater control over query results.

    Conclusions:

    • The fuzzy query translation method significantly improves the friendliness and flexibility of relational database systems.
    • This approach empowers inexperienced users to interact with databases more effectively using natural language-like fuzzy terms.
    • The alpha-cuts based method provides a robust mechanism for handling uncertainty in database query formulation.