Online Shopping Customer Behaviour Analysis using centrality measures

Kavitha H.M, Suraj Duncan T, P. Ravikumar, Varun E
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引用次数: 3

Abstract

Now the world is completely filled with the data. Each every action is generating the huge amount of data called as Big data. Analysis, processing of Big data itself is a big field emerging nowadays called as data science. Ecommerce field is growing much more and people are becoming lazier to walk through shops for purchasing. A huge competation in ecommerce field to attract people towards purchasing by providing them more and more offers. In order to achieve that need to identify the regular customer to shopping websites and providingthem more offers increases the revenue of ecommerce field this is achieved through mining the shopping dataset.This paper deals the technique that identifies the key customer using the centrality measures by considering his transaction data of shopping dataset.
使用中心性测量的网上购物顾客行为分析
现在这个世界完全充满了数据。每一个动作都会产生大量的数据,我们称之为大数据。大数据的分析、处理本身就是当今新兴的一个大领域,被称为数据科学。电子商务领域发展得越来越快,人们越来越懒于在商店里购物。电子商务领域的巨大竞争,通过提供越来越多的优惠来吸引人们购买。为了实现这一目标,需要识别购物网站的常规客户并为他们提供更多的优惠,从而增加电子商务领域的收入,这是通过挖掘购物数据集来实现的。本文研究了利用购物数据集中关键客户交易数据的中心性度量来识别关键客户的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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