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As data become big and complex, it is also more challenging to data scientists to extract useful information in a timely fashion. Although many tools and packages are available to them, it is crucial to have a high productive and scalable big data analytics platform to carry out their daily work productively. The objective for our work is to build such a productive data analytics cloud platform by...
The fast growing data volume poses significant challenges as well as opportunities to research and industry. Data scientists and domain experts demand high productive and high-performance data analytics platform, which will alleviate their work, tackle these challenges, and find more opportunities from data. The objective of our research is to build such a productive data analytics cloud platform...
High Performance Computing (HPC) has been a dominated technology used in seismic data processing at the petroleum industry. However, with the increasing data size and varieties, traditional HPC focusing on computation meets new challenges. Researchers are looking for new computing platforms with a balance of both performance and productivity, as well as featured with big data analytics capability...
With the advent of the era of big data, O2O as a new industry of making an integration of online and offline effectively, attracts more and more people to start to talk about this topic. In this article, after exploring the past academic research for two years, it is considered to select the local service industry and study the problem of the O2O industry, such as “Meituan.com”.
With the volume of port data growing at an unprecedented rate, analyzing and extracting knowledge from large-scale data sets have become a new challenge in decision making. But, the application of standard data mining tools in such data sets is not straightforward. Hence, we develop a parallel large-scale knowledge reduction method based on rough set for knowledge acquisition using MapReduce in this...
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