A fuzzy deductive object-oriented database model

Bostan, B
Yazıcı, Adnan
Object-oriented and deductive database models are two different paradigms in database modeling. As has been pointed out by many researchers, [1], [6], [14], each of these data models has its shortcomings when dealing with database/knowledge-base applications. Therefore, it is believed that combining object-oriented concepts with those of deductive database modeling results in a powerful data model especially for knowledge-intensive applications. In these applications, it is important to model and manipulate complex objects and relationships with uncertain properties. This study introduces a fuzzy deductive object-oriented database model for representation and deduction of complex and fuzzy objects. Although various types of uncertainty, such as null, incomplete and fuzzy types are considered, we mainly focus on fuzzy types. Deduction is used to cope with complex relationships and to derive new information. In addition, the implementation of this model using Poplog environment is briefly described.


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We use a Fuzzy Petri Net (FPN) structure to represent knowledge and model the behavior in our intelligent object-oriented database environment, which integrates fuzzy, active and deductive rules with database objects. However, the behavior of a system can be unpredictable due to the rules triggering or untriggering each other (non-termination). Intermediate and final database states may also differ according to the order of rule executions (non-confluence). In order to foresee and solve problematic behavior...
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Multi-relational learning has become popular due to the limitations of propositional problem definition in structured domains and the tendency of storing data in relational databases. As patterns involve multiple relations, the search space of possible hypotheses becomes intractably complex. Many relational knowledge discovery systems have been developed employing various search strategies, search heuristics and pattern language limitations in order to cope with the complexity of hypothesis space. In this w...
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Citation Formats
B. Bostan and A. Yazıcı, “A fuzzy deductive object-oriented database model,” 1998, p. 1361, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62498.