| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4944190 | Information Sciences | 2017 | 22 Pages |
Abstract
We derive the result by giving the variances of RN and RE estimators. Each step of the derivation is supported and demonstrated by simulation studies assuming power law distributions. Then we use 18 real-world networks to verify the result. Furthermore, we show that the performance of random walk (RW) sampling is data dependent and can be significantly worse than RN and RE. More specifically, RW can estimate online social networks but not Web graphs due to the difference of the graph conductance.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jianguo Lu, Hao Wang,