scholarly journals Parallel Strategy for the Large-Scale Data Streams Processing

Author(s):  
Ya-Juan Yuan ◽  
Guo-Jie Ma
2020 ◽  
Vol 204 ◽  
pp. 106186 ◽  
Author(s):  
Fang Liu ◽  
Yanwei Yu ◽  
Peng Song ◽  
Yangyang Fan ◽  
Xiangrong Tong

2016 ◽  
Vol 194 ◽  
pp. 107-116 ◽  
Author(s):  
Jingsong Shan ◽  
Jianxin Luo ◽  
Guiqiang Ni ◽  
Zhaofeng Wu ◽  
Weiwei Duan

Author(s):  
Jon R. Wright ◽  
Gregg T. Vesonder ◽  
Tamraparni Dasu

In an enterprise setting, a major challenge for any data mining operation is managing data streams or feeds, both data and metadata, to ensure a stable and certifiably accurate flow of data. Data feeds in this environment can be complex, numerous and opaque. The management of frequently changing data and metadata presents a considerable challenge. In this paper, we articulate the technical issues involved in the task of managing enterprise data and propose a multi-disciplinary solution, derived from fields such as knowledge engineering and statistics, to understand, standardize, and automate information acquisition and quality management in preparation for enterprise mining.


2020 ◽  
Vol 171 ◽  
pp. 107402
Author(s):  
S. Sukhanov ◽  
R. Wu ◽  
C. Debes ◽  
A.M. Zoubir

Author(s):  
Mahardhika Pratama ◽  
Choiru Za’in ◽  
Edwin Lughofer ◽  
Eric Pardede ◽  
Dwi A.P. Rahayu

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