From: Evaluation of linear relaxations in Ad Network optimization for online marketing
Setting 1 | Setting 2 | Setting 3 | Setting 4 | |
---|---|---|---|---|
Scenario 1 | ||||
B 2 | ∞ | B 1=500 | B 1=500 | B 1=500 |
T 1 | 50,000 | 50,000 | 50,000 | 50,000 |
T 2 | ∞ | 50,000 | 50,000 | 50,000 |
ctr1 | \(\frac {B_{1}}{T_{1}}=0.01\) | 0.01 | 0.01 | 0.01 |
ctr2 | 0 | 0 | 0.1ctr1=0.001 | 0.5ctr1=0.005 |
Performance | 1.0181 | 1.0181 | 1.0148 | 1.0060 |
Scenario 2 | ||||
B 2 | B 1=500 | B 1=500 | B 1=500 | B 1=500 |
T 1 | 500 | 50,000 | 50,000 | 50,000 |
T 2 | 500 | 50,000 | 50,000 | 50,000 |
ctr1 | \(\frac {B_{1}}{T_{1}+T_{2}}\,=\,0.5\) | \(\frac {B_{1}}{T_{1}+T_{2}}\,=\,0.005\) | 0.005 | 0.005 |
ctr2 | ctr1 = 0.5 | ctr1 = 0.005 | 0.9ctr1 = 0.0045 | 0.5ctr1 = 0.0025 |
Performance | 1.0128 | 1.0181 | 1.0123 | 1.0027 |