From: A method for exploring implicit concept relatedness in biomedical knowledge network
 | Pruning mask | Edges | Average count | Average percentage |
---|---|---|---|---|
No Mask | R all (1,0,0)a | 971,585 | 1054.6 | 100 % |
Mask 1 | R 1(0,0,0),R rest (1,0,0)b | 969,001 | 566 | 26.78 % |
Mask 2 | R 2(0,0,0),R rest (1,0,0) | 971,501 | 460.5 | 22.77 % |
Mask 3 | R 3(0,0,0),R rest (1,0,0) | 964,792 | 90.7 | 4.22 % |
Mask 4 | R 4(0,0,0),R rest (1,0,0) | 965,000 | 124 | 46.65 % |
Mask 5 | R 5(0,0,0),R rest (1,0,0) | 965,000 | 66.6 | 8.94 % |
Mask 6 | R 6(0,0,0),R rest (1,0,0) | 810,489 | 1.5 | 0.21 % |
Mask 7 | R 7(0,0,0),R rest (1,0,0) | 810,489 | 954.6 | 53.17 % |
Mask 8 | R 9(0,0,0),R rest (1,0,0) | 965,189 | 27.9 | 2.96 % |
Mask 9 | R all (1,0,0.4) | 965,718 | 753.3 | 63.01 % |
Mask 10 | R 8(1,0.4,0) | 382,972 | 4.5 | 0.24 % |
Mask 11 | R 1(0,0,0),R rest (1,0.2,0.35) | 615,921 | 136.7 | 19.56 % |
Mask 12 | R 5(0,0,0),R rest (1,0.2,0) | 615,179 | 476.5 | 20.57 % |