Abstract
Users often have vague or imprecise ideas when searching the database. Thus, they might like to issue fuzzy queries for possibly retrieving. Based on fuzzy sets theory and the knowledge base related to the application domain, this paper proposes an approach translating the fuzzy query into the precise query and extending the query criteria ranges in order to provide approximate answers to the user. The fuzzy condition is first defined by a fuzzy number with membership function, and then is translated into the precise condition by using the (-cut operation of fuzzy number. The tuples satisfying the fuzzy query are finally ranked according to their satisfaction degree.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, S., Chaudhuri, S., Das, G., Gionis, A.: Automated ranking of database query results. ACM Transactions on Database Systems 28(2), 140–174 (2003)
Bosc, P., Pivert, O.: SQLf: a relational database language for fuzzy querying. IEEE Transactions on Fuzzy Systems 3(1), 1–17 (1995)
Bosc, P., Galibourg, M., Hamon, G.: Fuzzy querying with SQL: extensions and implementation aspects. Fuzzy Sets Systems 28, 333–349 (1988)
Bordogna, G., Psaila, G.: Extending SQL with customizable soft selection conditions. In: 20th ACM Symposium on Applied Computing, pp. 1107–1111. ACM Press, Santa Fe (2005)
Chen, S.M., Jong, W.T.: Fuzzy query translation for relational database systems. IEEE Transactions Systems, Man, and Cybernetics-Part B: Cybernetics 27(4), 714–721 (1997)
Chaudhuri, S., Das, G., Hristidis, V.: Probabilistic information retrieval approach for ranking of database query results. ACM Transaction on Database Systems 31(3), 1134–1168 (2006)
Goncalves, M., Tineo, L.: SQLf flexible querying extension by means of the norm SQL2. In: 10th IEEE International Conference on Fuzzy Systems, pp. 473–476. IEEE Press, New York (2001)
Goncalves, M., Tineo, L.: SQLf3: an extension of SQLf with SQL3 features. In: 10th IEEE International Conference on Fuzzy Systems, pp. 477–480. IEEE Press, New York (2001)
Ma, Z.M., Yan, L.: Generalization of strategies for fuzzy query translation in classical relational databases. Information and Software Technology 49(2), 172–180 (2007)
Nakajima, H., Sogoh, T., Arao, M.: Fuzzy database language and library: Fuzzy extension to SQL. In: 2nd IEEE International Conference on Fuzzy Systems, pp. 477–482. IEEE Press, San Francisco (1993)
Tahani, V.: A conceptual framework for fuzzy querying processing: a step toward very intelligent databases systems. Information Processing Management 13, 289–303 (1997)
Wong, M., Leung, K.: A fuzzy database-query language. Information Systems 15(5), 583–590 (1990)
Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ma, Z.M., Meng, X. (2008). A Knowledge-Based Approach for Answering Fuzzy Queries over Relational Databases. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5178. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85565-1_77
Download citation
DOI: https://doi.org/10.1007/978-3-540-85565-1_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85564-4
Online ISBN: 978-3-540-85565-1
eBook Packages: Computer ScienceComputer Science (R0)