Decision Making in the Multi-Dimensional Trust by Mining Huge Volume of unstructured E-Commerce Feedback Comments

Authors

  • Dr. Kalli Srinivasa Nageswara Prasad  Professor, Department of CSE, GVVR Institute of Technology, Bhimavaram. Andhra Pradesh, India
  • Sravan Kumar Vulchi  M.Tech. CSE Department Student, GVVR Institute of Technology, Bhimavaram. Andhra Pradesh, India

Keywords:

Electronic commerce, text mining, Big Data, Hadoop, Volume

Abstract

Information of extreme size, diversity and complexity – is everywhere. This disruptive phenomenon is destined to help organizations drive innovation by gaining new and faster insight into their customers. Market and Technology has its own way of implementation of the strategic decision policy. These days’ data mining in the trend o the E-commerce plays the role of the market, as the trend is shifting from classical trend to the electronics trend which in turn we call as E-commerce. If we approach the model of axis model of decision making cannot be without data and information. Hence In this Paper we put forward the concept of the feedback from customer as open text which mined with the specific purpose to study the customer need in the E-commerce market. Vendors like Amazon and Alibaba more customer centric rather to market centric, hence the data will help them what is the trend the customer need rather to the market. In the context, we have implemented the no-sql database based approach to retrieve information in a pattern which the client or customer need. The Divide and Conquer with Map reduced program enables us to reach the destination with the robustness, performance oriented and best of the timely technology solution.

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Published

2016-04-30

Issue

Section

Research Articles

How to Cite

[1]
Dr. Kalli Srinivasa Nageswara Prasad, Sravan Kumar Vulchi, " Decision Making in the Multi-Dimensional Trust by Mining Huge Volume of unstructured E-Commerce Feedback Comments, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 2, Issue 2, pp.373-377, March-April-2016.