Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

The Role of Domain Knowledge in a Large Scale Data Mining Project

  • Conference paper
  • First Online:
Methods and Applications of Artificial Intelligence (SETN 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2308))

Included in the following conference series:

Abstract

Data Mining techniques have been applied in many application areas. A Data Mining project has been often described as a process of automatic discovery of new knowledge from large amounts of data. However the role of the domain knowledge in this process and the forms that this can take, is an issue that has been given little attention so far. Based on our experience with a large scale Data Mining industrial project we present in this paper an outline of the role of domain knowledge in the various phases of the process. This project has led to the development of a decision support expert system for a major Telecommunications Operator. The data mining process is described in the paper as a continuous interaction between explicit domain knowledge, and knowledge that is discovered through the use of data mining algorithms. The role of the domain experts and data mining experts in this process is discussed. Examples from our case study are also provided.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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.

Similar content being viewed by others

References

  1. Langley P., Simon H.A., Applications of Machine Learning and Rule Induction, Com. of the ACM, 38 (11), (1995), 55–64.

    Google Scholar 

  2. Brachman R. Anand T., “The Process of Knowledge Discovery in Databases: A Human-Centered Approach”, Advances in Knowledge Discovery & Data Mining, AAAI Press & The MIT Press: California, 996, (1996), 37–57.

    Google Scholar 

  3. Domingos P., “The Role of Occam’s Razor in Knowledge Discovery”, Data Mining and Knowledge Discovery, an International Journal, Kluwer Academic Publishers, Vol.3, (1999), 409–425.

    Article  Google Scholar 

  4. Yoon S.-C., Henschen L. J., Park E. K., Makki S., Using Domain Knowledge in Knowledge Discovery, Proc. ACM Conf. CIKM’ 99 1 l/99 Kansas City, MO, USA, pp. 243–250.

    Google Scholar 

  5. Anand S. S., Bell D. A., Hughes J. G., The Role of Domain Knowledge in Data Mining, Proc. ACM CIKM’95, Baltimore MD USA, pp. 37–43.

    Google Scholar 

  6. Van Heijst G., Schreiber G., CUE: Ontology Based Knowledge Acquisition, Proc. 8th European Knowledge Acquisition Workshop, EKAW 94, vol 867 of Lecture Notes in AI, pp. 178–199, Springer-Verlag, Berlin/Heidelberg (1994).

    Google Scholar 

  7. Wielinga B.J., Schreiber A.T., Breuker J.A., KADS: A modelling approach to knowledge Engineering, Knowledge Acquisition, 4(1), 5–53 (1992).

    Article  Google Scholar 

  8. Fayyad U.M., Piatetsky-Shapiro G., and Smyth P., The KDD Process for Extracting Useful Knowledge from Volumes of Data, Communications of the ACM, 39(11), (1996)

    Google Scholar 

  9. Liebowitz J., Knowledge management and its link to artificial intelligence, Expert Systems with Applications 20, (2001) 1–6

    Article  Google Scholar 

  10. Gur Ali, O.F., Wallace, W.A., Bridging the gap between business objectives and parameters of data mining algorithms, Decision Support Systems, 21, (1997) 3–15

    Article  Google Scholar 

  11. Daskalaki S., Kopanas I., Goudara M., Avouris N., Data Mining for Decision Support on Customer Insolvency in Telecommunications Business, European Journal of Operations Research, submitted (2001)

    Google Scholar 

  12. Ankerst M., Ester M., Kriegel H-P, Towards and Effective Cooperation of the Computer and the user in Classification, ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD’2000), Boston, MA (2000)

    Google Scholar 

  13. Williams G. J. and Huang Z, Modelling the KDD Process, A Four Stage Process and Four Element Model, TR DM 96013, CSIRO, Canberra, Australia (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kopanas, I., Avouris, N.M., Daskalaki, S. (2002). The Role of Domain Knowledge in a Large Scale Data Mining Project. In: Vlahavas, I.P., Spyropoulos, C.D. (eds) Methods and Applications of Artificial Intelligence. SETN 2002. Lecture Notes in Computer Science(), vol 2308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46014-4_26

Download citation

  • DOI: https://doi.org/10.1007/3-540-46014-4_26

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43472-6

  • Online ISBN: 978-3-540-46014-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics