Implementation of SQL Symbolic Extensions on Object-Relational Database

Authors

  • Johnny Villalobos-Murillo Escuela de Informática, Universidad Nacional. Heredia, Costa Rica., Costa Rica
  • Steven Brenes-Chavarría Escuela de Informática, Universidad Nacional. Heredia, Costa Rica., Costa Rica

DOI:

https://doi.org/10.15359/ru.29-2.2

Keywords:

Database, extension, relational-object, SQL, symbolic-object

Abstract

This article proposes extend the SQL language with new data types and operators for create and manipulate symbolic objects directly in the database. The functionality of the proposed extension is validated by performing transformations of classical symbolic objects to relational data bases of large data. For users not familiar with the SQL language, a final user interface is built to facilitate and guide the process of symbolic transformation.

References

Billard, L. (2006). Symbolic Data Analysis: Conceptual Statistics And Data Mining. New York: Wiley. DOI http://dx.doi.org/10.1002/9780470090183

Bock, H-H., & Diday, E. (2000). Analysis of Symbolic Data. Exploratory methods for extracting statistical information from complex data. Springer Verlag, 425.

Codd, E. (1970). A relational model of data for large shared data banks. Communications of the ACM, 377-387. DOI http://dx.doi.org/10.1145/362384.362685

Diday, E. (2009). The state of the art in symbolic data analysis: overview and future. Obtenido de http://media.wiley.com/product_data/excerpt/36/04700188/0470018836-1.pdf

Moore, R. (1979). Methods and Applications of Interval Analysis. Philadelphia, USA: Society for Industrial and Applied Mathematics (SIAM)

Rodríguez, O. (2000). The Knowledge Mining Suite (KMS). San José, Costa Rica: University of Costa Rica and Predisoft International S.A

The PostgreSQL Global Development Group. (2012). PostgreSQL Developer's Guide. Obtenido de http://www.postgresql.org

Published

2015-07-01

Issue

Section

Original scientific papers (evaluated by academic peers)

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