COMBINING SEMANTIC TECHNOLOGIES AND DATA MINING TO ENDOW BSS/OSS SYSTEMS WITH INTELLIGENCE - Particularization to an International Telecom Company Tariff System

Javier Martínez Elicegui, Germán Toro del Valle, Marta de Francisco Marcos

2010

Abstract

Businesses need to "reduce costs" and improve their “time-to-market" to compete in a better position. Systems must contribute to these two goals through good designs and technologies that give them agility and flexibility towards change. Semantics and Data Mining are two key pillars to evolve the current legacy systems towards smarter systems that adapt to changes better. In this article we present some solutions to evolve the existing systems, where the end user has the possibility of modifying the functioning of the systems incorporating new business rules in a Knowledge Base.

References

  1. Turban, E. et al, 2006. Decision Support and Business Intelligence Systems. Prentice-Hall, Inc.
  2. Semantic Web Case Studies and Use Cases. W3C, (http://www.w3.org/2001/sw/sweo/public/UseCases)
  3. Baader,F., Horrocks, I., Sattler, U., 2004. Handbook on Ontologies, Springer.
  4. Davies, J., Fensel, D., van Harmelen, F., 2002. Towards the Semantic Web: Ontology-driven Knowledge Management. John Wiley and Sons, Inc.
  5. Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C., 1995 Multivariate Data Analysis (4th Ed.): with Readings. Prentice-Hall, Inc.
  6. Fayyad, U.,M. et al, 1996. Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press.
  7. Witten, Ian H., Frank Eibe. 2005. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann Publishers.
  8. McGuiness, D. L., van Harmelen, F., 2004. OWL Web Ontology Language Overview. W3C
  9. Recommendation. (www.w3.org/TR/owl-features)
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Paper Citation


in Harvard Style

Martínez Elicegui J., Toro del Valle G. and de Francisco Marcos M. (2010). COMBINING SEMANTIC TECHNOLOGIES AND DATA MINING TO ENDOW BSS/OSS SYSTEMS WITH INTELLIGENCE - Particularization to an International Telecom Company Tariff System . In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-8425-06-5, pages 350-355. DOI: 10.5220/0002975603500355


in Bibtex Style

@conference{iceis10,
author={Javier Martínez Elicegui and Germán Toro del Valle and Marta de Francisco Marcos},
title={COMBINING SEMANTIC TECHNOLOGIES AND DATA MINING TO ENDOW BSS/OSS SYSTEMS WITH INTELLIGENCE - Particularization to an International Telecom Company Tariff System},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2010},
pages={350-355},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002975603500355},
isbn={978-989-8425-06-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - COMBINING SEMANTIC TECHNOLOGIES AND DATA MINING TO ENDOW BSS/OSS SYSTEMS WITH INTELLIGENCE - Particularization to an International Telecom Company Tariff System
SN - 978-989-8425-06-5
AU - Martínez Elicegui J.
AU - Toro del Valle G.
AU - de Francisco Marcos M.
PY - 2010
SP - 350
EP - 355
DO - 10.5220/0002975603500355