KNOWLEDGE EXTRACTION GUIDED BY ONTOLOGIES - Database Marketing Application

Filipe Mota Pinto, Teresa Guarda

Abstract

The knowledge extraction in large databases has being known as a long term and interactive project. In spite of such complexity and different options for the knowledge achievement, there is a research opportunity that could be explored, throughout the ontologies support. Then this support may be used for knowledge sharing and reuse. This paper describes a research of an ontological approach for leveraging semantic content of ontologies to improve knowledge extraction in a oil company marketing databases. We attain to analyze how ontologies and knowledge discovery process may interoperate and present our efforts to propose a possible framework for a formal integration.

References

  1. Bernstein, A., Provost, F., and Hill, S. (2005). Toward intelligent assistance for a data mining process. IEEE Transactions knowledge & data engineering, 17(4).
  2. Domingos, P. (2003). Prospects and challenges for multirelational data mining. SIGKDD Explorer Newsletter, 5(1):80-83.
  3. Pinto, Filipe. Mota, Gago, P., and Santos, M. F. (2009). Marketing database knowledge extraction In IEEE 13th International Conference on Intelligent Engineering Systems 2009.
  4. Pinto, Mota Filipe. and Santos, M. F. (2009). Database marketing supported by ontologies . In 11th ICEIS.
  5. Gottgtroy, P., Kasabov, N., and MacDonell, S. (2004). An ontology driven approach for knowledge discovery in biomedicine.
  6. Grassl Wolfgang (2007) “The reality of brands: Towards an ontology of marketing. American Journal of Economics and Sociology, 58(2):313-319, April.
  7. Gruber, T. R. (1993). A translation approach ontology specifications. Knowledge Acquisition, 5:199-220.
  8. Knublauch Holger, Horridge M., Noy N, and Wang H (2005) “The Protégé OWL Experience”, Workshop on OWL: Experiences & Directions, Galway, Ireland
  9. Han, J. and Kamber, M. (2001). Data mining: concepts & Techniques. Morgan Kaufman, San Francisco, CA.
  10. Horrocks, I., Patel-Schneider, S., Grosof, B., and Dean, M. (2004). Swrl: A semantic web rule language - combining owl and ruleml. Technical report, W3C.
  11. Phillips, J. and Buchanan, B. G. (2001). Ontology-guided knowledge discovery in databases. In ACM, editor, International Conference On Knowledge Capture , p 123-130. I C. On Knowledge Capture.
  12. Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2000). Analysis of recommendation algorithms for ecommerce. In Proc 2nd ACM Conf e-Commerce.
  13. Shepard David. (1998)“Database Marketing”. São Paulo: Makron Books.
  14. Witten, I. H. and Frank, E. (2000). Data Mining: Practical Machine Learning Tools and Technique. The Morgan Kaufmann Series in Data Management Systems, 2nd edition.
  15. Zhou Xuan, Geller James, and Perl Yehoshua and Halper Michael.(2009) “An Application Intersection Marketing Ontology”, Theoretical Computer Science, pp 143-163.LNCS. Springer Berlin.
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Paper Citation


in Harvard Style

Mota Pinto F. and Guarda T. (2011). KNOWLEDGE EXTRACTION GUIDED BY ONTOLOGIES - Database Marketing Application . In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-53-9, pages 320-325. DOI: 10.5220/0003555103200325


in Bibtex Style

@conference{iceis11,
author={Filipe Mota Pinto and Teresa Guarda},
title={KNOWLEDGE EXTRACTION GUIDED BY ONTOLOGIES - Database Marketing Application},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2011},
pages={320-325},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003555103200325},
isbn={978-989-8425-53-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - KNOWLEDGE EXTRACTION GUIDED BY ONTOLOGIES - Database Marketing Application
SN - 978-989-8425-53-9
AU - Mota Pinto F.
AU - Guarda T.
PY - 2011
SP - 320
EP - 325
DO - 10.5220/0003555103200325