PROGRESSIVE RECOMMENDATION ENGINE FOR BIG DATA ANALYTICS IMPROVISING BUSINESS VALUE

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Every Second build up data amounting and generating huge repository of data, thanks to improved Modern Information Systems technologies in data sciences such as IoT, Cloud Computing, Networks and Grid based systems. Decision making based on these data becomes challenging as it requires different coordinated analysis from data repository. The dataset selected for the analysis requires effective performance and Scalability. It should also deliver business value considering the atomic transactions in databases solving irrelevant data. This paper suggests a basic module using recommendation engine to determine content easily with various mining techniques to improve the business value. A dataset from online shopping such as a home appliance purchase along with Consumer behavioural data is collected for mining and then sorted in big data environment to provide relatively accurate recommendations to the consumer to exact product. Open-source platforms are favoured for this particular implementation for understanding and portability. The results are well grooved in perspective nature to demonstrate the relevancy of the specific item searched from the dataset. The same can be frame worked with higher proficiency in terms of additional dataset if required for selection when multiple datasets are processed for greater introspection and accuracy.

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Keywords

Big Data, Scalability, recommendation engine, business value, consumer.