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Graph Sample and Hold: A Framework for Big-Graph Analytics
Published on Oct 07, 20142125 Views
Sampling is a standard approach in big-graph analytics; the goal is to efficiently estimate the graph properties by consulting a sample of the whole population. A perfect sample is assumed to mirror e
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Chapter list
Graph Sample and Hold: A Framework for Big Graph Analytics00:00
Graphs: Rich Data Representation00:09
Studying and analyzing complex networks - 100:26
Studying and analyzing complex networks - 200:42
Motivation - 100:52
Motivation - 201:13
Motivation - 301:21
Motivation - 401:34
Related Work - Sampling - 101:45
Related Work - Sampling - 203:27
Related Work - Stream Sampling - 103:41
Related Work - Stream Sampling - 205:05
Graph-Sample-and-Hold: gSH (p, q) - 105:33
Graph-Sample-and-Hold: gSH (p, q) - 205:46
Graph-Sample-and-Hold: gSH (p, q) - 305:55
Graph-Sample-and-Hold: gSH (p, q) - 406:04
Graph-Sample-and-Hold: gSH (p, q) - 506:13
Graph-Sample-and-Hold: gSH (p, q) - 606:46
Uniform Random Sampling06:54
Graph-Sample-and-Hold: gSH (p, q) - 707:16
The Sampling - 107:32
The Sampling - 207:36
The Sampling - 307:54
The Sampling - 408:01
The Sampling - 508:02
The Sampling - 608:03
The Sampling - gSH (p, q) - 108:06
The Sampling - gSH (p, q) - 208:09
The Sampling - gSH (p, q) - 308:32
The Estimation - 108:34
The Estimation - 208:38
The Estimation - 308:57
The Estimation - 409:08
The Estimation - 509:24
The Estimation - 609:35
The Estimation - 709:50
The Estimation - 810:00
The Estimation - 910:14
The Estimation - 1010:25
The Estimation - 1110:45
Experiments - 111:00
Experiments - 211:08
Experiments - 311:31
Experiments - 411:39
Comparison to previous work - 112:25
Comparison to previous work - 212:47
Conclusion13:05
Future Work14:36
Thank you!15:20