Big Data Visualization Collaborative Filtering Algorithm Based on RHadoop

Lijun Cai, Xiangqing Guan, Peng Chi, Lei Chen and Jianting Luo

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 10, 271253

Abstract: With the rapid growth of various data, it is becoming increasingly important to extract useful information from big data. While the analysis tools of big data visualization is very rare, in this paper, we propose a new big data visualization algorithm analysis integrated model. The model integrates the processing of big data and the visualization of data as a whole. It is a good analysis tool of timely big data visualization. We use hadoop_1.X as the data storage and use R as the compiler environment in the model. If you are skilled in R, it is easy to design kinds of paralleling algorithms, and analyze and process the kinds of big data. Secondly we design and implement a paralleled collaborative filtering algorithm with the model. Finally we analyze the various performance indicators with kinds of experiments. The indicators show that the model has good scalability and easy operability, and contains all the advantages of Map Reduce. In conclusion, the big data visualization algorithm analysis integrated model has high performance to process and visualize the big data.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2015/271253 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:10:p:271253

DOI: 10.1155/2015/271253

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().