Skip to main content

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

  • 1729 Accesses

Abstract

With growing science and technology in manufacturing industry, an electronic database as grown in a diverse manner. In order to maintain, organizing and analyzing application-driven databases, a systematic approach of data analysis is essential. The most succeeded approach for handling these problems is through advanced database technologies and data mining approach. Building the database with advance technology and incorporating data mining aspect to mine the hidden knowledge for a specific application is the recent and advanced data mining application in the computer application domain. Here in this article, association rule analysis of data mining concepts is investigated on engineering materials database built with UML data modeling technology to extract application-driven knowledge useful for decision making in different design domain applications.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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

References

  1. Walls, M.D.: Data Modeling, 2nd Revised edn. URISA, Park Ridge (2007)

    Google Scholar 

  2. Han, J., Kamber, M., Pie, J.: Data Mining: Concepts and Techniques, 3rd edn. Margan Kaufmann, Burlington (2012)

    Google Scholar 

  3. Rajan, K.: Materials informatics. Mater. Today 8(10), 38–45 (2005)

    Google Scholar 

  4. Ashby, M.F.: Materials Selection in Mechanical Design, 3rd edn. Pergamon Press, Oxford (2005)

    Google Scholar 

  5. Doreswamy, Manohar, M.G., Hemanth, K.S.: Object-oriented database model for effective mining of advanced engineering materials data sets. In: The Second International Conference on Computer Science Engineering and Applications (CCSEA-2012), pp. 129–137 (2012)

    Google Scholar 

  6. Budinski, K.G.: Engineering Materials Properties and Selection, 5th edn. Prentice Hall Publishing, New York (2000)

    Google Scholar 

  7. Callister, W.D Jr.: Materials Science and Engineering, 5th edn. Wiley, New York (2000)

    Google Scholar 

  8. Umoh, U.A., Nwachukwu, E.O., Eyoh, I.J., Umoh, A.A.: Object oriented database management system: a UML design approach. Pacific J. Sci. Technol. 10(2), 355–365 (2009)

    Google Scholar 

  9. Satheesh, A., Patel, R.: Use of object-oriented concepts in databases for effective mining. Int. J. Comput. Sci. Eng. 1(3), 206–216 (2009)

    Google Scholar 

  10. Srikant, R., Agrawal, R.: Mining quantitative association rules in large relational tables. In: Proceedings of the ACM-SIGMOD: Conference on Management of Data, Montreal, Canada, June 1996

    Google Scholar 

  11. Watanabe, T., Takahashi, H.: A study on quantitative association rules mining algorithm based on clustering algorithm. Biomed. Soft Comput. Hum. Sci. 16(2), 59–67 (2011)

    Google Scholar 

  12. Online database for materials’ properties. http://www.makeitfrom.com/ (2012)

  13. Online material data obtained from literature research and from experiments performed during work on projects and doctoral thesis. http://www.matdat.com/ (2012)

  14. Online materials properties database. http://www.matweb.com/ (2012)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Doreswamy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer India

About this paper

Cite this paper

Doreswamy, Hemanth, K.S. (2014). Mining Knowledge from Engineering Materials Database for Data Analysis. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_127

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1602-5_127

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics