The Reproducible Data Reuse ( ReDaR ) Framework to Capture and Assess Multiple Data Streams

2021 ◽  
Vol 58 (1) ◽  
pp. 230-240
Author(s):  
Donald A. Keefer ◽  
Catherine L. Blake
Keyword(s):  
Data Streams ◽  
Data Reuse ◽  
Multiple Data ◽  
Multiple Data Streams

scholarly journals Comparing multiple data streams to assess free-floating carsharing use

2018 ◽  
Vol 32 ◽  
pp. 617-626 ◽  
Author(s):  
Grzegorz Wielinski ◽  
Martin Trépanier ◽  
Catherine Morency ◽  
Khandker Nurul Habib
Keyword(s):  
Data Streams ◽  
Multiple Data ◽  
Multiple Data Streams

Clustering Algorithm for Multiple Data Streams Based on Data Cloud Node

2013 ◽  
Vol 462-463 ◽  
pp. 247-250
Author(s):  
Sa Li ◽  
Liang Shan Shao
Keyword(s):  
Data Streams ◽  
Minimum Distance ◽  
Clustering Algorithm ◽  
Cloud Model ◽  
Data Sequence ◽  
Multiple Data ◽  
Multiple Data Streams ◽  
Model Algorithm

Multiple data streams clustering aims to clustering multiple data streams according to their similarity while tracking their changes with time . This paper proposes M_SCCStream algorithm based on cloud model. Algorithm introduces data cloud node structure with hierarchical characteristics to represent different granularity data sequence and takes the entropy indicated the degree of data changes. Algorithm finds micro_clustering with the minimum distance and then obtains the clustering result of multiple data streams through calculating the correlation degrees of micro_clustering. The experiment proves that the algorithm has higher quality and stability.

Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs

2007 ◽  
Vol 26 (8) ◽  
pp. 1834-1856 ◽  
Author(s):  
Henry Rolka ◽  
Howard Burkom ◽  
Gregory F. Cooper ◽  
Martin Kulldorff ◽  
David Madigan ◽  
...  
Keyword(s):  
Public Health ◽  
Data Streams ◽  
Applied Statistics ◽  
Research Needs ◽  
Multiple Data ◽  
Multiple Data Streams
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