Systematic Translation of Fuzzy Semantic Model (FSM) RETRIEVE Queries to Standard ANSI SQL for Enhanced RDBMS Interoperability

Zouhaier Brahmia, Asmaa Ben Ahmed Daho, Salem Chakhar, Fatima-Zohra Younsi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Fuzzy Semantic Model (FSM) provides a high-level RETRIEVE query language for managing data uncertainty, utilizing explicit Degree of Membership (d.o.m.) constraints for both entities and attributes. However, FSM's adoption is limited by its incompatibility with standard SQL, unlike prior fuzzy solutions that require proprietary extensions or lack the capacity for semantic structural mapping. We propose a systematic, phase-based algorithm for the complete translation of FSM RETRIEVE into standard ANSI SQL. Our algorithm formalizes two key mappings: (i) d.o.m. constraints (global and partial) are translated into crisp SQL predicates on dedicated columns; and (ii) complex attribute navigation (path expressions) is resolved into optimal primary key-foreign key joins. The resulting standard SQL queries ensure the preservation of FSM's integrity and allow FSM applications
Original languageEnglish
Title of host publicationThe 7th International Conference on Artificial Intelligence and Smart Environments (ICAISE'2025). November, 06-08 2025, Hammamet, Tunisia.
PublisherSpringer
Publication statusAccepted for publication - 30 Nov 2025

Publication series

NameSpringer Lecture Notes in Networks & Systems
PublisherSpringer

Keywords

  • Fuzzy Database
  • Query Translation
  • Fuzzy Semantic Model
  • Standard SQL
  • Object-Relational Mapping

Fingerprint

Dive into the research topics of 'Systematic Translation of Fuzzy Semantic Model (FSM) RETRIEVE Queries to Standard ANSI SQL for Enhanced RDBMS Interoperability'. Together they form a unique fingerprint.

Cite this