Mining Knowledge from Engineering Materials Database for Data Analysis

  • DoreswamyEmail author
  • K. S. Hemanth
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)


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.


Data mining Object-oriented Advanced engineering materials  Association rule 


  1. 1.
    Walls, M.D.: Data Modeling, 2nd Revised edn. URISA, Park Ridge (2007)Google Scholar
  2. 2.
    Han, J., Kamber, M., Pie, J.: Data Mining: Concepts and Techniques, 3rd edn. Margan Kaufmann, Burlington (2012)Google Scholar
  3. 3.
    Rajan, K.: Materials informatics. Mater. Today 8(10), 38–45 (2005)Google Scholar
  4. 4.
    Ashby, M.F.: Materials Selection in Mechanical Design, 3rd edn. Pergamon Press, Oxford (2005)Google Scholar
  5. 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. 6.
    Budinski, K.G.: Engineering Materials Properties and Selection, 5th edn. Prentice Hall Publishing, New York (2000)Google Scholar
  7. 7.
    Callister, W.D Jr.: Materials Science and Engineering, 5th edn. Wiley, New York (2000)Google Scholar
  8. 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. 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. 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 1996Google Scholar
  11. 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. 12.
    Online database for materials’ properties. (2012)
  13. 13.
    Online material data obtained from literature research and from experiments performed during work on projects and doctoral thesis. (2012)
  14. 14.
    Online materials properties database. (2012)

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceMangalore UniveristyMangaloreIndia

Personalised recommendations