Novel Model for the Computation of Linguistic Hedges in Database Queries
Article Sidebar
Published:
Oct 19, 2011
Keywords:
Fuzzy Query, Linguistic variable, Membership value, Alpha-cut, SQL
Main Article Content
Abstract
Most query languages are designed to retrieve information from databases containing precise and certain data using precisely specified commands. Due to the advancements in various kinds of data repositories in the recent years, there is a steep increase in complex queries. Most of the complex Queries are uncertain and vague. The existing Structured Query Language exhibits its inefficiency in handling these complex Queries. This paper proposes a model to handle the complexities by using fuzzy set theory. In this model, the Fuzzy Query with linguistic hedges is converted into Crisp Query, by deploying an application layer over the Structured Query Language.
Article Details
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Section
Computing
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References
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https://doi.org/10.1002/int.4550090505
Wilma Penzo, Rewriting Rules to Permeate Complex Similarity and Fuzzy Queries within a Relational Database System, IEEE Transactions on Knowledge and Data Engineering, VOL 17, NO 2, February 2005,.255-270, 2005.
African Journal of Information and Communication Technology, Vol. 6, No. 1, September 2011.
Bosc, P. and Pivert, O. and Farquhar, K. () Integrating Fuzzy Queries into an Existing Database Management System: An Example, International Journal of Intelligent Systems, 1994.
https://doi.org/10.1002/int.4550090507
Gogolla, M. and Hohenstein, U. Towards a Semantic View of an Extended Entity-Relationship Model, ACM Transactions on Database Systems, 16, 369-416, 1991.
https://doi.org/10.1145/111197.111200
Lee, D., Kim, M.H., Lee-Kwang, H., and Lee, Y-H. A Fuzzyfication of the Relational Data Model in: Moon,S.and Ikeda, H. (Eds) Database Systems for Advanced Applications '93, World Scientific: Singapore, 360- 367, 1993. African Journal of Information and Communication Technology, Vol. 6, No. 1, September 2011
Lee, D.H., and Kim, M.H. Accommodating Subjective Vagueness Through a Fuzzy Extension to the Relational Data Model, Information Systems, 18, 6, 363-374, 1993.
https://doi.org/10.1016/0306-4379(93)90013-Q
Lee, D.H., and Kim, M.H. Extending Semantics of Relational Operators for Vague Queries, Microprocessing and Micro- programming, 39, 165-168, 1993.
https://doi.org/10.1016/0165-6074(93)90080-5
Nan-Chen Hsieh, Answers to Database Queries Concerning Imprecise Information in Logical Fuzzy Relational Databases, Tamkang Journal of Scinece & Engineering, Vol. 7, No 3.pp.149 -150, 2004.
Raju, K.V.S.V.N. and Majumdar, A.K. Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database System, ACM Transactions on Database Systems, 13, 2, 129-166, 1988.
https://doi.org/10.1145/42338.42344
Takahashi, Y. Fuzzy Database Query Languages and Their Relational Completeness Theorem, IEEE Transactions on Knowledge and Data Engineering, 5, 1,122-125, 1993
https://doi.org/10.1109/69.204096
Timothi J.Ross Fuzzy Logic with Engineering Applications, McGraw-Hill Book Co – Singapore, 1997.
Villa, M. A., Cubero, J. C., Medina, J. M. and Pons, O. A Logic Approach to Fuzzy Relational Databases, International Journal of Intelligent Systems, 9, 449-460, 1994.
https://doi.org/10.1002/int.4550090505
Wilma Penzo, Rewriting Rules to Permeate Complex Similarity and Fuzzy Queries within a Relational Database System, IEEE Transactions on Knowledge and Data Engineering, VOL 17, NO 2, February 2005,.255-270, 2005.
African Journal of Information and Communication Technology, Vol. 6, No. 1, September 2011.