A fuzzy knowledge-based system for intelligent retrieval

Murat Koyuncu, Adnan Yazici

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)


For many knowledge-intensive applications, it is important to develop an environment that permits flexible modeling and fuzzy querying of complex data and knowledge including uncertainty. With such an environment, one can have intelligent retrieval of information and knowledge, which has become a critical requirement for those applications. In this paper, we introduce a fuzzy knowledge-based (FKB) system along with the model and the inference mechanism. The inference mechanism is based on the extension of the Rete algorithm to handle fuzziness using a similarity-based approach. The proposed FKB system is used in the intelligent fuzzy object-oriented database (IFOOD) environment, in which a fuzzy object-oriented database is used to handle large scale of complex data while the FKB system is used to handle knowledge of the application domain. Both the fuzzy object-oriented database system and the fuzzy knowledge-based system are based on the object-oriented concepts to eliminate data type mismatches. The aim of this paper is mainly to introduce the FKB system of the IFOOD environment.

Original languageEnglish
Pages (from-to)317-330
Number of pages14
JournalIEEE Transactions on Fuzzy Systems
Issue number3
Publication statusPublished - Jun 1 2005


  • Flexible querying
  • Fuzzy set theory
  • Inference mechanism
  • Knowledge-based systems
  • Object-oriented databases
  • Uncertainty

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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