Abstract
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.
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Prasuna, P.M., Ramadevi, Y., Vinay Babu, A. (2016). Distributed Data Mining for Modeling and Prediction of Skin Condition in Cosmetic Industry—A Rough Set Theory Approach. In: Bhramaramba, R., Sekhar, A. (eds) Application of Computational Intelligence to Biology. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-10-0391-2_9
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