Ranking of Product on Big Data using Apache Spark

Smita M. Deshpande, Rakesh S. Shirsath

Abstract


Recommendation system has been used by enormous users. It used commonly in recent years, and are used in a variable areas in many popular applications which comprise of movies, songs, bulletin, files, research courses, online shopping, social networking sites, and products recommendation. Gradually, the extent of consumers, products and facts has mature rapidly, the big data scrutiny problem for examination of recommender systems. Here we are evaluating most efficient recommendation system. Conventional recommender systems frequently suffer from deficiency of scalability, efficiency and real time recommendation problems while processing or analysing documents taking place at huge scale. To get rid from these problems, a recommendation system is implemented in Apache Hadoop and Spark including MapReduce paradigm for Bigdata. Proposed Framework can have considerable enhancement in performance associated to traditional tools.

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References


Gejianxin and Liu jiaomin, Software Test Cases Recommendation System

Research based on Collaborative Filtering, IEEESNPD 2016, May 30-

June 1, 2016.

artosz Kupisz and Olgierd Unold, Collaborative Filtering Recommendation

Algorithm based on Hadoop and Spark, IEEE 2015.

Riyaz P A, Surekha Mariam Varghese, A Scalable Product Recommendations

using Collaborative Filtering in Hadoop for Bigdata, International

Conference on Emerging Trends in Engineering, Science and Technology

(ICETEST- 2015).

Dheerajkumar Bokde, Sheetal Girase and Debajyoti Mukhopadhyay, An

Approach to A University Recommendation by Multi-Criteria Collaborative

Filtering and Dimensionality Reduction Techniques, IEEE International

Symposium on Nanoelectronic and Information Systems, 2015.

ZhiyangJia,Wei Gao, Yuting Yang, Xu Chen, User-based Collaborative

Filtering for Tourist Attraction Recommendations, IEEE 2015International

Conference on Computational Intelligence Communication Technology,

-1- 4799-6023-1/15 2015 IEEE DOI 10.1109/CICT.2015.20.

Jyoti Gupta, JayantGadge, Performance Analysis of Recommendation

System Based On Collaborative Filtering and Demographics, IEEE

International Conference on Communication, Information Computing

Technology (ICCICT), 978-1-4799-5521- 3, 2015 DOI: 10.1109/ICCICT.2015.7045675.

Suman Datta, Joydeep Dasy, Prosenjit Gupta and Subhashis Majumder,

SCARS: A Scalable Context- Aware Recommendation System, IEEE

FAN Lu, LI Hong, LI Changfeng, The improvement and implementation

of distributed item- based collaborative filtering algorithm on Hadoop,

Proceedings of the 34th Chinese Control ConferenceJuly 28-30, IEEE

Shunmei Meng, Wanchun Dou, Xuyun Zhang, and Jinjun Chen, KASR:

A Keyword Aware Service Recommendation Method on MapReduce for

Big Data Applications, IEEE 2014.

Kunhui Lin, Jingjin Wang, Meihong Wang, A Hybrid Recommendation

Algorithm Based on Hadoop, the 9th International Conference on

Computer Science Education (ICCSE 2014) August 22-24, 2014.

Yingya Zhang, Cheng Yang, ZhixiangNiu, A Research of Job Recommendation

System Based on Collaborative Filtering, Seventh International

Symposium on Computational Intelligence and Design, IEEE 2014.

Poonam Ghuli, Atanu Ghosh and Dr. Rajashree Shettar, A Collaborative

Filtering Recommendation Engine in a Distributed Environment, IEEE

Xiao Peng, Shao Liangshan, Li Xiuran, Improved collaborative filtering

algorithm in the research and application of personalized movie recommendations,

Fourth International Conference on Intelligent Systems

Design and Engineering Applications, IEEE 2013.

Suyun Wei, Ning Ye, Shuo Zhang , Xia Huang, Jian Zhu, Itembased

Collaborative Filtering Recommendation Algorithm Combining

Item Category with Interestingness Measure, International Conference on

Computer Science and Service System, IEEE 2012.

Michael D. Ekstrand, John T. Riedl and Joseph A. Konstan., Collaborative

Filtering Recommender Systems, Foundations and Trends R in

Human Computer Interaction Vol.4, No.2 (2010).

Wu Yueping and ZhengJianguo, A research of recommendation algorithm

based on cloud model, IEEE 2010.


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