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Intelligent Big Data Analytics: Adaptive E-Commerce Website Ranking Using Apriori Hadoop – BDAS-Based Cloud Framework

Intelligent Big Data Analytics: Adaptive E-Commerce Website Ranking Using Apriori Hadoop – BDAS-Based Cloud Framework
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Author(s): Dheeraj Malhotra (University of Kota, India), Neha Verma (I. K. Gujral Punjab Technical University, India), Om Prakash Rishi (University of Kota, India)and Jatinder Singh (DAV University, India)
Copyright: 2018
Pages: 18
Source title: Mobile Commerce: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-2599-8.ch014

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Abstract

With the explosive increase in regular E Commerce users, online commerce companies must have more customer friendly websites to satisfy the personalized requirements of online customer to progress their market share over competition; Different individuals have different purchase requirements at different time intervals and hence novel approaches are often required to be deployed by online retailers in order to identify the latest purchase requirements of customer. This research work proposes a novel MR apriori algorithm and system design of a tool called IMSS-SE, which can be used to blend benefits of Apriori-based Map Reduce framework with Intelligent technologies for B2C E-commerce in order to assist the online user to easily search and rank various E Commerce websites which can satisfy his personalized online purchase requirement. An extensive experimental evaluation shows that proposed system can better satisfy the personalized search requirements of E Commerce users than generic search engines.

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