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About the Performance of Fuzzy Querying Systems

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2012 Workshops (OTM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7567))

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Abstract

Traditional database systems suffer of rigidity. Use of fuzzy sets has been proposed for solving it. Nevertheless, there is certain resistance to adopt this, due the presumption that it adds undesired costs that worsen the performance and scalability of software systems. RDBMS are rather complex by themselves. Extensions for providing higher facilities, with a permissible performance and good scalability would be appreciated. In this paper, we achieve a formal statistics study of fuzzy querying performance. We considered two querying systems: SQLfi (loose coupling) and PostgreSQLf (tight coupling). Observed times for the later are very reasonable. It shows that it is possible to build high performance fuzzy querying systems.

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References

  1. Bosc, P., Pivert, O.: SQLf: A Relational Database Language for Fuzzy Quering. IEEE Transactions on Fuzzy Systems 3(1) (February1995)

    Google Scholar 

  2. Bosc, P., Pivert, O.: SQLf query functionality on top of a regular relational DBMS. In: Pons, O., Vila, M.A., Kacprzyk, J. (eds.) Knowledge Management in Fuzzy Databases (2000)

    Google Scholar 

  3. Aguilera, A., Cadenas, J., Tineo, L.: Fuzzy Querying Capability at Core of a RDBMS. In: Yan, L., Ma, Z. (eds.) Advanced Database Query Systems: Techniques, Applications and Technologies, pp. 160–184. IGI Global, New York (2011)

    Chapter  Google Scholar 

  4. Goncalves, M., Tineo, L.: SQLfi and its Applications. Avances en Sistemas e Informática, vol. 5(2) (2008); Medellin, ISSN 1657-7663

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  5. Goncalves, M., González, C., Tineo, L.: A New Upgrade to SQLf: Towards a Standard in Fuzzy Databases. In: Proc of DEXA 2009 Workshops (2009)

    Google Scholar 

  6. Timarán, R.: Arquitecturas de Integración del Proceso de Descubrimiento de Conocimiento con Sistemas de Gestión de Bases de Datos: un Estado del Arte. Ingeniería y Competitividad 3(2) (2001)

    Google Scholar 

  7. Raj, J.: The Art of Computer Systems Performance. John Wiley/Sons, Inc. (1991)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Aguilera, A., Cadenas, J.T., Tineo, L. (2012). About the Performance of Fuzzy Querying Systems. In: Herrero, P., Panetto, H., Meersman, R., Dillon, T. (eds) On the Move to Meaningful Internet Systems: OTM 2012 Workshops. OTM 2012. Lecture Notes in Computer Science, vol 7567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33618-8_94

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  • DOI: https://doi.org/10.1007/978-3-642-33618-8_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33617-1

  • Online ISBN: 978-3-642-33618-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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