Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Design of multivariable big data mobile analysis platform based on collaborative filtering recommendation algorithm

Design of multivariable big data mobile analysis platform based on collaborative filtering... In order to overcome the problems of poor accuracy and high data redundancy in the current big data analysis platform, this paper proposes and designs a multivariable big data mobile analysis platform based on collaborative filtering recommendation algorithm. The platform is divided into data acquisition layer, storage layer, processing and analysis layer and scheduling layer, introduces two ways of dimensionality reduction and recommendation to realise multivariable big data mining and analysis. User behaviour analysis and data item behaviour analysis of the dimension-reduced data are carried out, and multi-level coordination is used to complete the construction of multivariable big data mobile analysis platform. The experimental results show that the accuracy of the platform's big data analysis is always above 97%, and the accuracy of data mining analysis is stronger. The acceleration ratio is always above 2, the response speed is faster, the user satisfaction is about 96%. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Autonomous and Adaptive Communications Systems Inderscience Publishers

Design of multivariable big data mobile analysis platform based on collaborative filtering recommendation algorithm

Loading next page...
 
/lp/inderscience-publishers/design-of-multivariable-big-data-mobile-analysis-platform-based-on-0wvX1duwYJ
Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1754-8632
eISSN
1754-8640
DOI
10.1504/IJAACS.2020.109811
Publisher site
See Article on Publisher Site

Abstract

In order to overcome the problems of poor accuracy and high data redundancy in the current big data analysis platform, this paper proposes and designs a multivariable big data mobile analysis platform based on collaborative filtering recommendation algorithm. The platform is divided into data acquisition layer, storage layer, processing and analysis layer and scheduling layer, introduces two ways of dimensionality reduction and recommendation to realise multivariable big data mining and analysis. User behaviour analysis and data item behaviour analysis of the dimension-reduced data are carried out, and multi-level coordination is used to complete the construction of multivariable big data mobile analysis platform. The experimental results show that the accuracy of the platform's big data analysis is always above 97%, and the accuracy of data mining analysis is stronger. The acceleration ratio is always above 2, the response speed is faster, the user satisfaction is about 96%.

Journal

International Journal of Autonomous and Adaptive Communications SystemsInderscience Publishers

Published: Jan 1, 2020

There are no references for this article.