DMK-Medoid Heuristic Product Ranking in Online Market

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