Skip to main content
SpringerLink
Log in

ODMQL: Object Data Mining Query Language

  • Conference paper
  • First Online:
Objects and Databases (SODB 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1944))

Included in the following conference series:

Abstract

Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. The emerging data mining tools and systems lead to the demand of a powerful data mining query language. The concepts of such a language for relational databases are discussed before. With the increasing popularity of object-oriented databases, it is important to design a data mining query language for such databases. The main objective of this paper is to propose an Object Data Mining Query Language (ODMQL) for object-oriented databases as an extension to the Object Query Language (OQL) proposed by the Object Data Management Group (ODMG) as a standard query language for object-oriented databases. The proposed language is implemented as a feature of an experimental object-oriented database management system that is developed as a testbed for research issues of object-oriented databases.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. Agrawal, T. Imielinski, and A. Swami. Mining Association Rules between Sets of Items in Large Databases. In Proceedings of 1993 ACM-SIGMOD International Conference on Management of Data, pages 207–216, May 1993.

    Google Scholar 

  2. R. Agrawal, M. Mehta, J. Shafer, R. Srikant, A. Arning, and T. Bollinger. The Quest Data Mining System. In Proceedings of 1996 International Conference on Data Mining and Knowledge Discovery (KDD’96), pages 244–249, Portland, Oregon, August 1996.

    Google Scholar 

  3. R. Agrawal and R. Srikant. Fast Algorithms for Mining Association Rules. In Proceedings of 1994 International Conference on Very Large Databases, pages 487–499, Santiago, Chile, September 1994.

    Google Scholar 

  4. E. Bertino and L. Martino. Object-Oriented Database Systems. Addison-Wesley, 1994.

    Google Scholar 

  5. C. Brunk, J. Kelly, and R. Kohavi. MineSet: An Integrated System for Data Mining. In Proceedings of Third International Conference on Data Mining and Knowledge Discovery (KDD’97), pages 135–138, Newport Beach, California, August 1997.

    Google Scholar 

  6. R.G.G. Cattell. The Object Database Standard: ODMG-93 (Release 1.2). Morgan Kaufmann, 1996.

    Google Scholar 

  7. U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth. From Data Mining to Knowledge Discovery: An Overview. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 1–34. AAAI / MIT Press, 1996.

    Google Scholar 

  8. S.A. Fouad, A.A. Saad, and M.G. Elfeky. ALEX Object-Oriented Database Management System. Published in ICCTA’99 International Conference on Computers: Theory and Applications, Alexandria, Egypt, August 1999.

    Google Scholar 

  9. J. Han, J. Chiang, S. Chee, J. Chen, Q. Chen, S. Cheng, W. Gong, M. Kamber, G. Liu, K. Koperski, Y. Lu, N. Stefanovic, L. Winstone, B. Xia, O.R. Zaiane, S. Zhang, and H. Zhu. DBMiner: A System for Data Mining in Relational Databases and Data Warehouses. In Proceedings of CASCON’97, Toronto, Canada, November 1997.

    Google Scholar 

  10. J. Han and Y. Fu. Discovery of Multiple-Level Association Rules from Large Databases. In Proceedings of 1995 International Conference on Very Large Databases, pages 420–431, Zurich, Switzerland, September 1995.

    Google Scholar 

  11. J. Han, Y. Fu, W. Wang, K. Koperski, and O. Zaiane. DMQL: A Data Mining Query Language for Relational Databases. 1996 SIGMOD’96 Workshop on Research Issues on Data Mining and Knowledge Discovery (DMKD’96), Montreal, Canada, June 1996.

    Google Scholar 

  12. J. Han, S. Nishio, H. Kawano, and W. Wang. Generalized-Based Data Mining in Object-Oriented Databases Using an Object Cube Model. In Data and Knowledge Engineering, 25(1-2), pages 55–97, 1998.

    Article  MATH  Google Scholar 

  13. T. Imielinski and H. Mannila. A Database Perspective on Knowledge Discovery. In Communications of the ACM, No. 11, pages 58–64, November 1996.

    Google Scholar 

  14. W. Klösgen. Explora: A Multipattern and Multistrategy Discovery Assistant. In U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 249–271. AAAI / MIT Press, 1996.

    Google Scholar 

  15. M. Mehta, R. Agrawal, and J. Rissanen. SLIQ: A Fast Scalable Classifier for Data Mining. In Proceedings of 1996 International Conference on Extending Database Technology, Avignon, France, March 1996.

    Google Scholar 

  16. A.A. Saad and G.M. Badr. The ALEX Object Manager. In Proceedings of ISCC’97 Second IEEE Symposium on Computers and Communications, pages 200–204, Alexandria, Egypt, July 1997.

    Google Scholar 

  17. R. Srikant and R. Agrawal. Mining Generalized Association Rules. In Proceedings of 1995 International Conference of Very Large Databases, pages 407–419, Zurich, Switzerland, September 1995.

    Google Scholar 

  18. L. Winstone, W. Wang and J. Han. Multiple-Level Data Classification in Large Databases. Submitted for publication, March 1996.

    Google Scholar 

  19. T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An Efficient Data Clustering Method for Very Large Databases. In Proceedings of 1996 ACM-SIGMOD International Conference on Management of Data, Montreal, Canada, June 1996.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science and Automatic Control Department Faculty of Engineering, Alexandria University, EGYPT

    Mohamed G. Elfeky (Ph.D. student), Amani A. Saad & Souheir A. Fouad

  2. Department of Computer Sciences, Purdue University, USA

    Mohamed G. Elfeky (Ph.D. student)

Authors
  1. Mohamed G. Elfeky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amani A. Saad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Souheir A. Fouad
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland

    Klaus Dittrich

  2. Dipartimento di Informatica e Scienze dell’Informazione, Università di Genova, via Dodecaneso 35, 16146, Genova, Italy

    Giovanna Guerrini  & Isabella Merlo  & 

  3. Departament d ′Informàtica i Enginyeria Industrial, Universitat de Lleida, C.Jaume II,69, 25001, Lleida, Spain

    Marta Oliva

  4. Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, MÒdul C 6,C.Jordi Girona Salgado 1-3, 08034, Barcelona, Spain

    M.Elena Rodriguez

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Elfeky, M.G., Saad, A.A., Fouad, S.A. (2001). ODMQL: Object Data Mining Query Language. In: Dittrich, K., Guerrini, G., Merlo, I., Oliva, M., Rodriguez, M. (eds) Objects and Databases. SODB 2000. Lecture Notes in Computer Science, vol 1944. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44677-X_9

Download citation

  • DOI: https://doi.org/10.1007/3-540-44677-X_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41664-7

  • Online ISBN: 978-3-540-44677-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation