A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations

Date

1996-09-11

Author

Yazıcı, Adnan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

199
views

0
downloads

In this paper we first introduce a new definition for the conformance of tuples existing in a fuzzy database relation. Then we give the formal definitions of fuzzy functional and multivalued dependencies on the basis of the conformance values presented here. Secondly, we list the inference rules after showing that both fuzzy functional and multivalued dependencies are consistent, that is, they reduce to those of the classic functional and multivalued dependencies when crisp attributes are involved. Finally, we show that the inference rules presented here are sound and complete for the family of functional and multivalued dependencies in fuzzy database relations.

Subject Keywords

Relational databases, Spatial databases, Fuzzy set theory, Data engineering, Hamming weight, Fuzzy sets

URI

https://hdl.handle.net/11511/62650

Conference Name

Proceedings of IEEE 5th International Fuzzy Systems

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Using fuzzy Petri nets for static analysis of rule-bases Bostan-Korpeoglu, B; Yazıcı, Adnan (2004-01-01) 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...
A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations Sozat, MI; Yazıcı, Adnan (Elsevier BV, 2001-01-15) This paper first introduces the formal definitions of fuzzy functional and multivalued dependencies which are given on the basis of the conformance values presented here. Second, the inference rules are listed after both fuzzy functional and multivalued dependencies are shown to be consistent, that is, they reduce to those of the classic functional and multivalued dependencies when crisp attributes are involved. Finally, the inference rules presented here are shown to be sound and complete for the family of...
A new hybrid multi-relational data mining technique Toprak, Seda Dağlar; Toroslu, İ. Hakkı; Department of Computer Engineering (2005) 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...
A neuro-fuzzy MAR algorithm for temporal rule-based systems Sisman, NA; Alpaslan, Ferda Nur; Akman, V (1999-08-04) This paper introduces a new neuro-fuzzy model for constructing a knowledge base of temporal fuzzy rules obtained by the Multivariate Autoregressive (MAR) algorithm. The model described contains two main parts, one for fuzzy-rule extraction and one for the storage of extracted rules. The fuzzy rules are obtained from time series data using the MAR algorithm. Time-series analysis basically deals with tabular data. It interprets the data obtained for making inferences about future behavior of the variables. Fu...
A Trie-structured Bayesian Model for Unsupervised Morphological Segmentation Kurfalı, Murathan; Ustun, Ahmet; CAN BUĞLALILAR, BURCU (2017-04-23) In this paper, we introduce a trie-structured Bayesian model for unsupervised morphological segmentation. We adopt prior information from different sources in the model. We use neural word embeddings to discover words that are morphologically derived from each other and thereby that are semantically similar. We use letter successor variety counts obtained from tries that are built by neural word embeddings. Our results show that using different information sources such as neural word embeddings and letter s...

Citation Formats

A. Yazıcı, “A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations,” New Orleans, LA, USA, 1996, p. 1611, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62650.