Distributed Data Mining for Modeling and Prediction of Skin Condition in Cosmetic Industry—A Rough Set Theory Approach

  • P. M. PrasunaEmail author
  • Y. Ramadevi
  • A. Vinay Babu
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)


Cosmetic industry is proliferating rapidly these days expanding its business globally with spatial distribution. However to rejuvenate a product to deal with a specific problem, analyzing data at the local level is not sufficient as the influencing factors of facial skin issues may vary from region to region. This leads to the situation where one needs to analyze the data in distributed environment in which local models are merged and further mined at the central node to derive the global modal which gives the adequate information to have better understanding of the skin problem thereby helping the industry to know what are the most common problems the people are suffering from and what type of products they are expecting from the industry. This paper discusses how to mine the cosmetic data in distributed environment using rough set theory.


Distributed data mining Rough set theory Local modal Global modal Discretization Mean roughness Distance relevance Maximum attributes dependency 


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© The Author(s) 2016

Authors and Affiliations

  1. 1.JNTUHyderabadIndia
  2. 2.CBITHyderabadIndia
  3. 3.JNTUHCEHyderabadIndia

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