期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2017
卷号：6
期号：3
页码：399-403
出版社：Shri Pannalal Research Institute of Technolgy
摘要：As an internet is spreading out of its bound the demand of online transaction is also getting considerably increased. Now the demand is fast and direct to home service very flexibly. So the ultimate research is online shopping. Online shopping is the method of effective transaction between money and goods .Which is done by user without spending large time of span. Products of Flip kart, Amazon, Snap deal, big basket are analyzed with opinion mining. Customer spends more time when purchasing the product on online by reading all the reviews before buying these products. This paper proposed novel approaches to rank the website efficiently by the mining of genuine reviews of the above specified websites. The deciding factors of these websites include user rating and reviews. In this paper intentional to the website reviews datasets persist analyzed by using simple k-means and x-means clustering algorithms are compared to find the time and cluster instance
关键词：Data Mining; K- means and x-means cluster algorithm; unsupervised learning; time; and instance; opinion mining.
