Extension of relational management systems with data mining capabilities

Juan F. Martinez; Anita Wasilewska; Michael Hadjimichael; Covadonga Fernandez; Ernestina Menasalvas

doi:10.1007/3-540-45813-1_55

Extension of relational management systems with data mining capabilities

Juan F. Martinez
, Anita Wasilewska
, Michael Hadjimichael
, Covadonga Fernandez
, Ernestina Menasalvas

Computer Science

Technical University of Madrid
Naval Research Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The relational model provides simple methods for data analysis, such as query and reporting tools. Data mining systems also provide data analysis capabilities. However, there is no uniform model which handles the representation and mining of data in such a way as to provide a standardization of inputs, outputs, and processing. In this paper we present a model of a data mining operator and a data mining structure that can be implemented over a relational database management system in the same way that multidimensional structures have been implemented.

Original language	English
Title of host publication	Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings
Editors	James J. Alpigini, James F. Peters, Andrzej Skowron, Ning Zhong
Publisher	Springer Verlag
Pages	421-424
Number of pages	4
ISBN (Print)	9783540442745
DOIs	https://doi.org/10.1007/3-540-45813-1_55
State	Published - 2002
Event	3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002 - Malvern, United States Duration: Oct 14 2002 → Oct 16 2002

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2475
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002
Country/Territory	United States
City	Malvern
Period	10/14/02 → 10/16/02

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10.1007/3-540-45813-1_55

Cite this

Martinez, J. F., Wasilewska, A., Hadjimichael, M., Fernandez, C., & Menasalvas, E. (2002). Extension of relational management systems with data mining capabilities. In J. J. Alpigini, J. F. Peters, A. Skowron, & N. Zhong (Eds.), Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings (pp. 421-424). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2475). Springer Verlag. https://doi.org/10.1007/3-540-45813-1_55

Martinez, Juan F. ; Wasilewska, Anita ; Hadjimichael, Michael et al. / Extension of relational management systems with data mining capabilities. Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings. editor / James J. Alpigini ; James F. Peters ; Andrzej Skowron ; Ning Zhong. Springer Verlag, 2002. pp. 421-424 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Extension of relational management systems with data mining capabilities",

abstract = "The relational model provides simple methods for data analysis, such as query and reporting tools. Data mining systems also provide data analysis capabilities. However, there is no uniform model which handles the representation and mining of data in such a way as to provide a standardization of inputs, outputs, and processing. In this paper we present a model of a data mining operator and a data mining structure that can be implemented over a relational database management system in the same way that multidimensional structures have been implemented.",

author = "Martinez, \{Juan F.\} and Anita Wasilewska and Michael Hadjimichael and Covadonga Fernandez and Ernestina Menasalvas",

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language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Martinez, JF, Wasilewska, A, Hadjimichael, M, Fernandez, C & Menasalvas, E 2002, Extension of relational management systems with data mining capabilities. in JJ Alpigini, JF Peters, A Skowron & N Zhong (eds), Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2475, Springer Verlag, pp. 421-424, 3rd International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002, Malvern, United States, 10/14/02. https://doi.org/10.1007/3-540-45813-1_55

Extension of relational management systems with data mining capabilities. / Martinez, Juan F.; Wasilewska, Anita; Hadjimichael, Michael et al.
Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings. ed. / James J. Alpigini; James F. Peters; Andrzej Skowron; Ning Zhong. Springer Verlag, 2002. p. 421-424 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2475).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Extension of relational management systems with data mining capabilities

AU - Martinez, Juan F.

AU - Wasilewska, Anita

AU - Hadjimichael, Michael

AU - Fernandez, Covadonga

AU - Menasalvas, Ernestina

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2002.

PY - 2002

Y1 - 2002

N2 - The relational model provides simple methods for data analysis, such as query and reporting tools. Data mining systems also provide data analysis capabilities. However, there is no uniform model which handles the representation and mining of data in such a way as to provide a standardization of inputs, outputs, and processing. In this paper we present a model of a data mining operator and a data mining structure that can be implemented over a relational database management system in the same way that multidimensional structures have been implemented.

AB - The relational model provides simple methods for data analysis, such as query and reporting tools. Data mining systems also provide data analysis capabilities. However, there is no uniform model which handles the representation and mining of data in such a way as to provide a standardization of inputs, outputs, and processing. In this paper we present a model of a data mining operator and a data mining structure that can be implemented over a relational database management system in the same way that multidimensional structures have been implemented.

UR - https://www.scopus.com/pages/publications/84942923161

U2 - 10.1007/3-540-45813-1_55

DO - 10.1007/3-540-45813-1_55

M3 - Conference contribution

AN - SCOPUS:84942923161

SN - 9783540442745

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 424

BT - Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings

A2 - Alpigini, James J.

A2 - Peters, James F.

A2 - Skowron, Andrzej

A2 - Zhong, Ning

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Martinez JF, Wasilewska A, Hadjimichael M, Fernandez C, Menasalvas E. Extension of relational management systems with data mining capabilities. In Alpigini JJ, Peters JF, Skowron A, Zhong N, editors, Rough Sets and Current Trends in Computing - 3rd International Conference, RSCTC 2002, Proceedings. Springer Verlag. 2002. p. 421-424. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45813-1_55

Extension of relational management systems with data mining capabilities

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