Abstract:
For the past two decades Web Technology (WT) and online shopping
has witnessed a monstrous growth. Everyday millions and billions of
online shopping websites are growing in the internet for purchasing all
types of commodities without disturbing the currency deliberately.
Product analysis is an inevitable and umpteen numbers of
methodologies are available in the existing world. In this paper,
commodity like washing machine is taken as a prime product for
analysis in the sites. Semantics has been formulated using different
online websites cart. K-medoid clustering (crisp) and fuzzy K-means
are employed for analyzing and mining a worthwhile cost and
warranty. While making the budget, applying distributed measures and
normalization in the above said semantics we have used Distributed
Measure (DM) K-Medoid architecture. After the two methodologies
crisp and fuzzy has been employed we arrive with that of the actuals.
Through variance both budget and actuals are gauged. For attribute
measures used gini and theil indexing in the semantics