Table 7 The Precision of different methods to predict missing links between nodes with no common neighbors under 10% and 20% probe set in 8 networks.
From: Predicting missing links in complex networks based on common neighbors and distance
Networks |
| PA | LP | Our |
| PA | LP | Our |
|---|---|---|---|---|---|---|---|---|
Karate | 10% | 0.05(224) | 0(0) | 0.353(207) | 20% | 0.064(116) | 0(0) | 0.351(169) |
Dolphins | 0(0) | 0(0) | 0.267(129) | 0.004(19) | 0(0) | 0.265(70) | ||
Polbook | 0(0) | 0(0) | 0.432(104) | 0(0) | 0(0) | 0.427(47) | ||
Word | 0(0) | 0(0) | 0.430(54) | 0.003(9) | 0(0) | 0.410(36) | ||
Neural | 0(0) | 0(0) | 0.441(25) | 0.005(8) | 0(0) | 0.457(20) | ||
Circuit | 0.002(5) | 0(0) | 0.081(17) | 0.004(3) | 0(0) | 0.059(12) | ||
0.001(2) | 0(0) | 0.340(21) | 0.004(4) | 0(0) | 0.335(9) | |||
Power | 0(1) | 0(0) | 0.059(5) | 0(0) | 0(0) | 0.047(3) |
- Precision = 
, which denotes the proportion of relevant links in the probe set 
. The results are the average of 20 realizations for each network, and probe set EP will be randomly removed every time. The highest value for each network is labeled in boldface. The numbers in the brackets denote the standard deviations. For example, 0.064 (116) denotes that the Precision value is 0.064 and the standard deviation is 116 × 10−4. The previous mentioned methods based on common neighbors cannot find any missing links between nodes with no common neighbors, and thus we do not list them here.
, which denotes the proportion of relevant links in the probe set 
. The results are the average of 20 realizations for each network, and probe set EP will be randomly removed every time. The highest value for each network is labeled in boldface. The numbers in the brackets denote the standard deviations. For example, 0.064 (116) denotes that the Precision value is 0.064 and the standard deviation is 116 × 10−4. The previous mentioned methods based on common neighbors cannot find any missing links between nodes with no common neighbors, and thus we do not list them here.