premise
string
hypothesis
string
label
int64
| Entity | Categorization | Conditions | | --- | --- | --- | | EndofSΟ€(jβˆ’1),i | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | left(2) | q∈Ijβˆ’1<br>(q∈III)∧(p∈II)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈II)jβˆ’1i+2 | | | right(3) | q∈IIjβˆ’1<br>(q∈III)∧(p∈I)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈I)jβˆ’1i+2 | |
| BeginningofSi,Ο€(j+1) | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | --- | --- | --- | | left(2) | q∈Ij+1<br>(q∈III)∧(p∈II)j+1iβˆ’2<br>(q∈IV)∧(p∈II)j+1i+2 | | | right(3) | q∈IIj+1<br>(q∈III)∧(p∈I)j+1iβˆ’2<br>(q∈IV)∧(p∈I)j+1i+2 | |
1
| Entity | Categorization | Conditions | | --- | --- | --- | | EndofSΟ€(jβˆ’1),i | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | left(2) | q∈Ijβˆ’1<br>(q∈III)∧(p∈II)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈II)jβˆ’1i+2 | | | right(3) | q∈IIjβˆ’1<br>(q∈III)∧(p∈I)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈I)jβˆ’1i+2 | |
| | k=3 | k=4 | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | h | q | r | t | q | r | t | q | | 1 | 3xβˆ’1 | 3x+3x+1 | βˆ’3xβˆ’1 | x+x+1 | x+2x+2 | βˆ’x | x+1 | | 2 | 2x+x+1<br>2<br>14x+3xβˆ’1<br>2<br>14x+17x+4 | x+x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1 | βˆ’x<br>βˆ’7xβˆ’2<br>7x+3 | 4x+2x+1 | 2x+2x+1 | βˆ’2x | 2x+x+2<br>2<br>6x+3x+1 | | 3 | 3x+2x+2 | x+x+1 | βˆ’x | 5x+9x+9<br>2<br>25x+15x+3<br>2<br>25x+25x+7 | x+2x+2<br>2<br>5x+4x+1<br>2<br>5x+6x+2 | βˆ’x<br>βˆ’5xβˆ’1<br>βˆ’5xβˆ’2 | 3x+2x+3<br>2<br>9x+6x+2<br>2<br>21x+8x+1<br>2<br>21x+22x+6 | | 4 | 4x+3x+3<br>2<br>12x+9x+2<br>2<br>28x+13x+1<br>2<br>28x+27x+6 | x+x+1<br>2<br>3x+3x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1 | βˆ’x<br>βˆ’3xβˆ’1<br>βˆ’7xβˆ’2<br>7x+3 | 8x+6x+3 | 2x+2x+1 | βˆ’2x | 4x+3x+4<br>2<br>28x+13x+2<br>2<br>28x+27x+7<br>2<br>52x+15x+1<br>2<br>52x+41x+8 | | 5 | 5x+4x+4<br>2<br>35x+18x+2<br>2<br>35x+32x+7<br>2<br>65x+22x+1<br>2<br>65x+48x+8<br>2<br>95x+56x+7<br>2<br>95x+94x+22 | x+x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1<br>2<br>13x+7x+1<br>2<br>13x+7x+1<br>2<br>19x+15x+3<br>2<br>19x+15x+3 | βˆ’x<br>βˆ’7xβˆ’2<br>7x+3<br>βˆ’13xβˆ’3<br>13x+4<br>βˆ’19xβˆ’7<br>19x+8 | 5x+9x+9<br>2<br>25x+15x+3<br>2<br>25x+25x+7<br>2<br>65x+37x+5<br>2<br>65x+63x+15<br>2<br>85x+23x+1<br>2<br>85x+57x+9 | x+2x+2<br>2<br>5x+4x+1<br>2<br>5x+6x+2<br>2<br>13x+10x+2<br>2<br>13x+10x+2<br>2<br>17x+8x+1<br>2<br>17x+8x+1 | βˆ’x<br>βˆ’5xβˆ’1<br>βˆ’5xβˆ’2<br>βˆ’13xβˆ’4<br>13x+6<br>βˆ’17xβˆ’3<br>17x+5 | 5x+4x+5<br>2<br>15x+12x+4<br>2<br>35x+18x+3<br>2<br>35x+32x+8<br>2<br>65x+22x+2<br>2<br>65x+48x+9<br>2<br>95x+56x+8<br>2<br>95x+94x+23 | | 6 | 6x+5x+5<br>2<br>18x+15+4<br>2<br>78x+29x+2<br>2<br>78x+55x+9<br>2<br>114x+71x+10<br>2<br>114x+109x+25<br>2<br>126x+33x+1<br>2<br>126x+75x+10 | x+x+1<br>2<br>3x+3x+1<br>2<br>13x+7x+1<br>2<br>13x+7x+1<br>2<br>19x+15x+3<br>2<br>19x+15x+3<br>2<br>21x+9x+1<br>2<br>21x+9x+1 | βˆ’x<br>βˆ’3xβˆ’1<br>βˆ’13xβˆ’3<br>13x+4<br>βˆ’19xβˆ’7<br>19x+8<br>βˆ’21xβˆ’4<br>21x+5 | 12x+10x+5<br>2<br>60x+26x+3<br>2<br>60x+46x+9<br>2<br>102x+31x+2<br>2<br>102x+65x+10 | 2x+2x+1<br>2<br>10x+6x+1<br>2<br>10x+6x+1<br>2<br>17x+8x+1<br>2<br>17x+8x+1 | βˆ’2x<br>βˆ’10xβˆ’2<br>10x+4<br>βˆ’17xβˆ’3<br>17x+5 | 6x+5x+6<br>2<br>18x+15x+5<br>2<br>42x+23x+4<br>2<br>42x+37x+9<br>2<br>78x+29x+3<br>2<br>78x+55x+10 |
0
| Entity | Categorization | Conditions | | --- | --- | --- | | EndofSΟ€(jβˆ’1),i | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | left(2) | q∈Ijβˆ’1<br>(q∈III)∧(p∈II)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈II)jβˆ’1i+2 | |
| right(3) | q∈IIjβˆ’1<br>(q∈III)∧(p∈I)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈I)jβˆ’1i+2 | | | --- | --- | --- | | BeginningofSi,Ο€(j+1) | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | left(2) | q∈Ij+1<br>(q∈III)∧(p∈II)j+1iβˆ’2<br>(q∈IV)∧(p∈II)j+1i+2 | | | right(3) | q∈IIj+1<br>(q∈III)∧(p∈I)j+1iβˆ’2<br>(q∈IV)∧(p∈I)j+1i+2 | |
1
| Entity | Categorization | Conditions | | --- | --- | --- | | EndofSΟ€(jβˆ’1),i | collinear(1) | q=pjβˆ’1iβˆ’1<br>q=pj+1i+1 | | left(2) | q∈Ijβˆ’1<br>(q∈III)∧(p∈II)jβˆ’1iβˆ’2<br>(q∈IV)∧(p∈II)jβˆ’1i+2 | |
| 2 | 2x+x+1<br>2<br>14x+3xβˆ’1<br>2<br>14x+17x+4 | x+x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1 | βˆ’x<br>βˆ’7xβˆ’2<br>7x+3 | 4x+2x+1 | 2x+2x+1 | βˆ’2x | 2x+x+2<br>2<br>6x+3x+1 | | --- | --- | --- | --- | --- | --- | --- | --- | | 3 | 3x+2x+2 | x+x+1 | βˆ’x | 5x+9x+9<br>2<br>25x+15x+3<br>2<br>25x+25x+7 | x+2x+2<br>2<br>5x+4x+1<br>2<br>5x+6x+2 | βˆ’x<br>βˆ’5xβˆ’1<br>βˆ’5xβˆ’2 | 3x+2x+3<br>2<br>9x+6x+2<br>2<br>21x+8x+1<br>2<br>21x+22x+6 | | 4 | 4x+3x+3<br>2<br>12x+9x+2<br>2<br>28x+13x+1<br>2<br>28x+27x+6 | x+x+1<br>2<br>3x+3x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1 | βˆ’x<br>βˆ’3xβˆ’1<br>βˆ’7xβˆ’2<br>7x+3 | 8x+6x+3 | 2x+2x+1 | βˆ’2x | 4x+3x+4<br>2<br>28x+13x+2<br>2<br>28x+27x+7<br>2<br>52x+15x+1<br>2<br>52x+41x+8 | | 5 | 5x+4x+4<br>2<br>35x+18x+2<br>2<br>35x+32x+7<br>2<br>65x+22x+1<br>2<br>65x+48x+8<br>2<br>95x+56x+7<br>2<br>95x+94x+22 | x+x+1<br>2<br>7x+5x+1<br>2<br>7x+5x+1<br>2<br>13x+7x+1<br>2<br>13x+7x+1<br>2<br>19x+15x+3<br>2<br>19x+15x+3 | βˆ’x<br>βˆ’7xβˆ’2<br>7x+3<br>βˆ’13xβˆ’3<br>13x+4<br>βˆ’19xβˆ’7<br>19x+8 | 5x+9x+9<br>2<br>25x+15x+3<br>2<br>25x+25x+7<br>2<br>65x+37x+5<br>2<br>65x+63x+15<br>2<br>85x+23x+1<br>2<br>85x+57x+9 | x+2x+2<br>2<br>5x+4x+1<br>2<br>5x+6x+2<br>2<br>13x+10x+2<br>2<br>13x+10x+2<br>2<br>17x+8x+1<br>2<br>17x+8x+1 | βˆ’x<br>βˆ’5xβˆ’1<br>βˆ’5xβˆ’2<br>βˆ’13xβˆ’4<br>13x+6<br>βˆ’17xβˆ’3<br>17x+5 | 5x+4x+5<br>2<br>15x+12x+4<br>2<br>35x+18x+3<br>2<br>35x+32x+8<br>2<br>65x+22x+2<br>2<br>65x+48x+9<br>2<br>95x+56x+8<br>2<br>95x+94x+23 | | 6 | 6x+5x+5<br>2<br>18x+15+4<br>2<br>78x+29x+2<br>2<br>78x+55x+9<br>2<br>114x+71x+10<br>2<br>114x+109x+25<br>2<br>126x+33x+1<br>2<br>126x+75x+10 | x+x+1<br>2<br>3x+3x+1<br>2<br>13x+7x+1<br>2<br>13x+7x+1<br>2<br>19x+15x+3<br>2<br>19x+15x+3<br>2<br>21x+9x+1<br>2<br>21x+9x+1 | βˆ’x<br>βˆ’3xβˆ’1<br>βˆ’13xβˆ’3<br>13x+4<br>βˆ’19xβˆ’7<br>19x+8<br>βˆ’21xβˆ’4<br>21x+5 | 12x+10x+5<br>2<br>60x+26x+3<br>2<br>60x+46x+9<br>2<br>102x+31x+2<br>2<br>102x+65x+10 | 2x+2x+1<br>2<br>10x+6x+1<br>2<br>10x+6x+1<br>2<br>17x+8x+1<br>2<br>17x+8x+1 | βˆ’2x<br>βˆ’10xβˆ’2<br>10x+4<br>βˆ’17xβˆ’3<br>17x+5 | 6x+5x+6<br>2<br>18x+15x+5<br>2<br>42x+23x+4<br>2<br>42x+37x+9<br>2<br>78x+29x+3<br>2<br>78x+55x+10 |
0
| n | n-k | m | q | d | t | r’ | r | GVR | Singleton | pk(bits) | sign(bits) | LP | Dual | DS | DA | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 57600 | 8640 | 130 | 1096 | 400 | 776 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 11520 | 1728 | 110 | 233 | 80 | 168 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 23040 | 3456 | 120 | 448 | 160 | 320 | | 20 | 10 | 24 | 2 | 2 | 3 | 5 | 8 | 6 | 10 | 24960 | 3008 | 190 | 370 | 104 | 226 | | 27 | 9 | 20 | 2 | 3 | 2 | 3 | 5 | 4 | 7 | 23328 | 1470 | 170 | 187 | 120 | 129 |
| 48 | 12 | 40 | 2 | 4 | 5 | 3 | 8 | 6 | 10 | 78720 | 2976 | ΒΏ600 | 340 | 164 | 114 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 50 | 10 | 42 | 2 | 5 | 5(2) | 2 | 7 | 5 | 9 | 70560 | 2800 | ΒΏ600 | 240 | 180 | 104 |
1
| n | n-k | m | q | d | t | r’ | r | GVR | Singleton | pk(bits) | sign(bits) | LP | Dual | DS | DA | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 57600 | 8640 | 130 | 1096 | 400 | 776 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 11520 | 1728 | 110 | 233 | 80 | 168 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 23040 | 3456 | 120 | 448 | 160 | 320 | | 20 | 10 | 24 | 2 | 2 | 3 | 5 | 8 | 6 | 10 | 24960 | 3008 | 190 | 370 | 104 | 226 | | 27 | 9 | 20 | 2 | 3 | 2 | 3 | 5 | 4 | 7 | 23328 | 1470 | 170 | 187 | 120 | 129 |
| 8-bit | 12-bit | 16-bit | 24-bit | 36-bit | | --- | --- | --- | --- | --- | | 14.19 | 13.26 | 13.13 | 13.84 | 14.90 | | 16.57 | 17.12 | 16.94 | 17.08 | 17.38 | | 21.97 | 22.76 | 23.91 | 25.89 | 27.53 | | 30.93 | 32.50 | 33.59 | 35.36 | 35.59 | | 15.06 | 15.43 | 15.64 | 16.07 | 16.78 | | 63.48 | 66.97 | 68.83 | 73.45 | 74.66 | | 56.67 | 71.41 | 76.50 | 80.40 | 82.73 | | 59.09 | 61.17 | 68.15 | 69.22 | 70.74 | | 71.86 | 75.12 | 80.33 | 81.70 | 83.16 |
0
| n | n-k | m | q | d | t | r’ | r | GVR | Singleton | pk(bits) | sign(bits) | LP | Dual | DS | DA | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 57600 | 8640 | 130 | 1096 | 400 | 776 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 11520 | 1728 | 110 | 233 | 80 | 168 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 23040 | 3456 | 120 | 448 | 160 | 320 |
| 20 | 10 | 24 | 2 | 2 | 3 | 5 | 8 | 6 | 10 | 24960 | 3008 | 190 | 370 | 104 | 226 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 27 | 9 | 20 | 2 | 3 | 2 | 3 | 5 | 4 | 7 | 23328 | 1470 | 170 | 187 | 120 | 129 | | 48 | 12 | 40 | 2 | 4 | 5 | 3 | 8 | 6 | 10 | 78720 | 2976 | ΒΏ600 | 340 | 164 | 114 | | 50 | 10 | 42 | 2 | 5 | 5(2) | 2 | 7 | 5 | 9 | 70560 | 2800 | ΒΏ600 | 240 | 180 | 104 |
1
| n | n-k | m | q | d | t | r’ | r | GVR | Singleton | pk(bits) | sign(bits) | LP | Dual | DS | DA | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 57600 | 8640 | 130 | 1096 | 400 | 776 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 11520 | 1728 | 110 | 233 | 80 | 168 | | 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 23040 | 3456 | 120 | 448 | 160 | 320 |
| 16.57 | 17.12 | 16.94 | 17.08 | 17.38 | | --- | --- | --- | --- | --- | | 21.97 | 22.76 | 23.91 | 25.89 | 27.53 | | 30.93 | 32.50 | 33.59 | 35.36 | 35.59 | | 15.06 | 15.43 | 15.64 | 16.07 | 16.78 | | 63.48 | 66.97 | 68.83 | 73.45 | 74.66 | | 56.67 | 71.41 | 76.50 | 80.40 | 82.73 | | 59.09 | 61.17 | 68.15 | 69.22 | 70.74 | | 71.86 | 75.12 | 80.33 | 81.70 | 83.16 |
0
| Method | N | E | C | | --- | --- | --- | --- | | SPINN-NPencoders | 80.6 | 88.2 | 85.5 | | mLSTM | 81.6 | 91.6 | 87.4 |
| word-wordattentionandaggregation | 83.7 | 92.1 | 86.7 | | --- | --- | --- | --- | | Ourmodelwithbi-LSTMencoders | 84.3 | 90.6 | 86.9 | | Ourmodelwithbtree-LSTMencoders | 84.8 | 93.2 | 87.4 |
1
| Method | N | E | C | | --- | --- | --- | --- | | SPINN-NPencoders | 80.6 | 88.2 | 85.5 | | mLSTM | 81.6 | 91.6 | 87.4 |
| Reference | Lexicon | LM | CH | SW | | --- | --- | --- | --- | --- | | Current | N | N | 26.4 | 17.2 | | Current | N | CharNG | 21.8 | 13.8 | | (ensemble) | Y | WordNG | 19.3 | 12.6 | | Current | Y | WordNG | 18.7 | 11.3 | | Current | Y | WordRNN | 17.7 | 10.2 |
0
| Method | N | E | C | | --- | --- | --- | --- | | SPINN-NPencoders | 80.6 | 88.2 | 85.5 | | mLSTM | 81.6 | 91.6 | 87.4 |
| word-wordattentionandaggregation | 83.7 | 92.1 | 86.7 | | --- | --- | --- | --- | | Ourmodelwithbi-LSTMencoders | 84.3 | 90.6 | 86.9 | | Ourmodelwithbtree-LSTMencoders | 84.8 | 93.2 | 87.4 |
1
| Method | N | E | C | | --- | --- | --- | --- | | SPINN-NPencoders | 80.6 | 88.2 | 85.5 | | mLSTM | 81.6 | 91.6 | 87.4 |
| Current | Y | WordNG | 18.7 | 11.3 | | --- | --- | --- | --- | --- | | Current | Y | WordRNN | 17.7 | 10.2 |
0
| Numbers | Category0 | Categoryvoid | | | | --- | --- | --- | --- | --- | | | Passed | Failed | Passed | Failed |
| Twitter | 12,681 | 2,228 | 21,443 | 4,123 | | --- | --- | --- | --- | --- | | Facebook | 7,586 | 1,287 | 21,715 | 3,579 | | Total | 20,267 | 3,515 | 43,158 | 7,702 |
1
| Numbers | Category0 | Categoryvoid | | | | --- | --- | --- | --- | --- | | | Passed | Failed | Passed | Failed |
| Category | Numberoftweets | | --- | --- | | Totaltweets | 3545 | | Tweetsinfavor | 964 | | Tweetsagainst | 647 | | Neutraltweets | 1934 |
0
| Numbers | Category0 | Categoryvoid | | | | --- | --- | --- | --- | --- | | | Passed | Failed | Passed | Failed |
| Twitter | 12,681 | 2,228 | 21,443 | 4,123 | | --- | --- | --- | --- | --- | | Facebook | 7,586 | 1,287 | 21,715 | 3,579 | | Total | 20,267 | 3,515 | 43,158 | 7,702 |
1
| Numbers | Category0 | Categoryvoid | | | | --- | --- | --- | --- | --- | | | Passed | Failed | Passed | Failed |
| Tweetsinfavor | 964 | | --- | --- | | Tweetsagainst | 647 | | Neutraltweets | 1934 |
0
| Name | NumberofEdges | NumberofTriangles | | --- | --- | --- | | cit-HepTh-dates | 38488 | 1418 | | wiki-Vote | 201524 | 608389 | | email-Enron | 367662 | 727044 |
| soc-sign-epinions | 1422420 | 4910076 | | --- | --- | --- | | flickrEdges | 4633896 | 107987357 | | web-Google | 8644102 | 13391903 | | cit-Patents | 33037894 | 7515023 |
1
| Name | NumberofEdges | NumberofTriangles | | --- | --- | --- | | cit-HepTh-dates | 38488 | 1418 | | wiki-Vote | 201524 | 608389 | | email-Enron | 367662 | 727044 |
| Entity | Ni | Vi | Mi | StructureType | | --- | --- | --- | --- | --- | | latlon | 1624984 | 1625197 | 1506465 | Identity | | lat | 1624984 | 1625192 | 1504469 | Identity | | lon | 1625061 | 1625725 | 1504619 | Identity | | place | 1741337 | 1741516 | 1504619 | Identity | | retweetID | 636455 | 636644 | 627163 | Identity | | reuserID | 720624 | 722148 | 676616 | Identity | | time | 2020000 | 2020000 | 35176 | Organization | | userID | 2020000 | 2020000 | 1711141 | Identity | | user | 2020000 | 2020000 | 1711143 | Identity | | word | 1976746 | 17180314 | 7838862 | Authority |
0
| Name | NumberofEdges | NumberofTriangles | | --- | --- | --- | | cit-HepTh-dates | 38488 | 1418 | | wiki-Vote | 201524 | 608389 | | email-Enron | 367662 | 727044 | | soc-sign-epinions | 1422420 | 4910076 | | flickrEdges | 4633896 | 107987357 |
| web-Google | 8644102 | 13391903 | | --- | --- | --- | | cit-Patents | 33037894 | 7515023 |
1
| Name | NumberofEdges | NumberofTriangles | | --- | --- | --- | | cit-HepTh-dates | 38488 | 1418 | | wiki-Vote | 201524 | 608389 | | email-Enron | 367662 | 727044 | | soc-sign-epinions | 1422420 | 4910076 | | flickrEdges | 4633896 | 107987357 |
| lat | 1624984 | 1625192 | 1504469 | Identity | | --- | --- | --- | --- | --- | | lon | 1625061 | 1625725 | 1504619 | Identity | | place | 1741337 | 1741516 | 1504619 | Identity | | retweetID | 636455 | 636644 | 627163 | Identity | | reuserID | 720624 | 722148 | 676616 | Identity | | time | 2020000 | 2020000 | 35176 | Organization | | userID | 2020000 | 2020000 | 1711141 | Identity | | user | 2020000 | 2020000 | 1711143 | Identity | | word | 1976746 | 17180314 | 7838862 | Authority |
0
| | Omniscient:<br>fulldistances | Agents’ordinalprefs<br>andfacilitylocations | Onlyagents’ordinal<br>prefs(lowerbounds) | | --- | --- | --- | --- | | Total(Sum)SocialChoice | 1 | 3 | 5(3) | | MedianSocialChoice | 1 | 3 | 5(5) | | MinWeightBipartiteMatching | 1 | 3 | n(3) | | EgalitarianBipartiteMatching | 1 | 3 | -(2) | | FacilityLocation | 1.488 | 3.976 | ∞(∞) |
| k-center | 2 | 5 | -(-) | | --- | --- | --- | --- | | k-median | 2.675 | 6.35 | -(Ω(n)) |
1
| | Omniscient:<br>fulldistances | Agents’ordinalprefs<br>andfacilitylocations | Onlyagents’ordinal<br>prefs(lowerbounds) | | --- | --- | --- | --- | | Total(Sum)SocialChoice | 1 | 3 | 5(3) | | MedianSocialChoice | 1 | 3 | 5(5) | | MinWeightBipartiteMatching | 1 | 3 | n(3) | | EgalitarianBipartiteMatching | 1 | 3 | -(2) | | FacilityLocation | 1.488 | 3.976 | ∞(∞) |
| pair | βˆ… | Ο‰1 | Ο‰2 | Ο‰3 | Ο‰4 | Ω | | --- | --- | --- | --- | --- | --- | --- | | (1,2) | 0 | 0.13975 | 0.23775 | 0.232 | 0.025 | 0.3655 | | (2,3) | 0 | 0.1765 | 0.05 | 0.10825 | 0.17 | 0.49525 | | (2,4) | 0 | 0.1 | 0.152 | 0.138 | 0.14875 | 0.46125 | | (3,4) | 0 | 0.1765 | 0.05 | 0.10825 | 0.17 | 0.49525 | | (4,5) | 0 | 0.241 | 0.234 | 0.152 | 0.06775 | 0.30525 |
0
| | Omniscient:<br>fulldistances | Agents’ordinalprefs<br>andfacilitylocations | Onlyagents’ordinal<br>prefs(lowerbounds) | | --- | --- | --- | --- | | Total(Sum)SocialChoice | 1 | 3 | 5(3) | | MedianSocialChoice | 1 | 3 | 5(5) | | MinWeightBipartiteMatching | 1 | 3 | n(3) |
| EgalitarianBipartiteMatching | 1 | 3 | -(2) | | --- | --- | --- | --- | | FacilityLocation | 1.488 | 3.976 | ∞(∞) | | k-center | 2 | 5 | -(-) | | k-median | 2.675 | 6.35 | -(Ω(n)) |
1
| | Omniscient:<br>fulldistances | Agents’ordinalprefs<br>andfacilitylocations | Onlyagents’ordinal<br>prefs(lowerbounds) | | --- | --- | --- | --- | | Total(Sum)SocialChoice | 1 | 3 | 5(3) | | MedianSocialChoice | 1 | 3 | 5(5) | | MinWeightBipartiteMatching | 1 | 3 | n(3) |
| (2,4) | 0 | 0.1 | 0.152 | 0.138 | 0.14875 | 0.46125 | | --- | --- | --- | --- | --- | --- | --- | | (3,4) | 0 | 0.1765 | 0.05 | 0.10825 | 0.17 | 0.49525 | | (4,5) | 0 | 0.241 | 0.234 | 0.152 | 0.06775 | 0.30525 |
0
| | 3newslices | 2newslices | | | | | --- | --- | --- | --- | --- | --- | | #runs | 1 | 2 | 3 | 4 | 5 | | initial | 8.73 | 9.01 | 8.89 | 6.54 | 6.98 |
| master<br>mintrack<br>maxtrack | 6.06<br>5.96<br>6.06 | 6.22<br>6.16<br>6.24 | 6.18<br>6.07<br>6.23 | 6.67<br>6.60<br>6.11 | 7.10<br>7.02<br>7.15 | | --- | --- | --- | --- | --- | --- | | total | 14.9 | 15.4 | 15.3 | 13.4 | 14.2 |
1
| | 3newslices | 2newslices | | | | | --- | --- | --- | --- | --- | --- | | #runs | 1 | 2 | 3 | 4 | 5 | | initial | 8.73 | 9.01 | 8.89 | 6.54 | 6.98 |
| 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 | | --- | --- | --- | | 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814Β·10 | 3219769<br>6427398<br>7<br>1.2827Β·10 | | 8<br>4<br>2 | 8.928Β·10<br>9<br>1.7856Β·10<br>9<br>3.5712Β·10 | 8.9394Β·10<br>9<br>1.7871Β·10<br>9<br>3.573Β·10 | | 8<br>4<br>2 | 1.2497Β·10<br>9<br>2.4995Β·10<br>9<br>4.9989Β·10 | 1.251Β·10<br>9<br>2.5005Β·10<br>9<br>4.9995Β·10 | | 8 | 6.4582Β·10 | 6.4651Β·10 |
0
| | 3newslices | 2newslices | | | | | --- | --- | --- | --- | --- | --- | | #runs | 1 | 2 | 3 | 4 | 5 |
| initial | 8.73 | 9.01 | 8.89 | 6.54 | 6.98 | | --- | --- | --- | --- | --- | --- | | master<br>mintrack<br>maxtrack | 6.06<br>5.96<br>6.06 | 6.22<br>6.16<br>6.24 | 6.18<br>6.07<br>6.23 | 6.67<br>6.60<br>6.11 | 7.10<br>7.02<br>7.15 | | total | 14.9 | 15.4 | 15.3 | 13.4 | 14.2 |
1
| | 3newslices | 2newslices | | | | | --- | --- | --- | --- | --- | --- | | #runs | 1 | 2 | 3 | 4 | 5 |
| 8<br>4<br>2 | 1.2497Β·10<br>9<br>2.4995Β·10<br>9<br>4.9989Β·10 | 1.251Β·10<br>9<br>2.5005Β·10<br>9<br>4.9995Β·10 | | --- | --- | --- | | 8 | 6.4582Β·10 | 6.4651Β·10 |
0
| Class | Guptaet.al | RGB | Depth | RGB-D | | --- | --- | --- | --- | --- | | bedroom | 79 | 79.06 | 78.01 | 82.72 | | kitchen | 74 | 65.09 | 60.38 | 75.47 | | livingroom | 47 | 73.83 | 33.64 | 75.70 | | bathroom | 67 | 89.66 | 81.03 | 96.55 | | diningroom | 47 | 96.36 | 50.91 | 96.36 | | office | 24 | 63.16 | 13.16 | 71.05 | | homeoffice | 8.3 | 70.83 | 0.00 | 62.50 | | classroom | 48 | 69.57 | 52.17 | 82.61 | | bookstore | 64 | 100.00 | 72.73 | 100.00 |
| others | 15 | 85.37 | 39.02 | 95.12 | | --- | --- | --- | --- | --- | | meandiag.cm. | 47 | 79.29 | 48.11 | 83.81 | | avg.accuracy | 58 | 77.52 | 55.81 | 82.42 |
1
| Class | Guptaet.al | RGB | Depth | RGB-D | | --- | --- | --- | --- | --- | | bedroom | 79 | 79.06 | 78.01 | 82.72 | | kitchen | 74 | 65.09 | 60.38 | 75.47 | | livingroom | 47 | 73.83 | 33.64 | 75.70 | | bathroom | 67 | 89.66 | 81.03 | 96.55 | | diningroom | 47 | 96.36 | 50.91 | 96.36 | | office | 24 | 63.16 | 13.16 | 71.05 | | homeoffice | 8.3 | 70.83 | 0.00 | 62.50 | | classroom | 48 | 69.57 | 52.17 | 82.61 | | bookstore | 64 | 100.00 | 72.73 | 100.00 |
| category | ours | | | | --- | --- | --- | --- | | bathtub | 0.0152 | 0.0266 | 0.0621 | | bed | 0.0068 | 0.0240 | 0.0617 | | chair | 0.0118 | 0.0238 | 0.0444 | | desk | 0.0122 | 0.0298 | 0.0731 | | dresser | 0.0038 | 0.0384 | 0.1558 | | monitor | 0.0103 | 0.0220 | 0.0783 | | nightstand | 0.0080 | 0.0248 | 0.2925 | | sofa | 0.0068 | 0.0186 | 0.0563 | | table | 0.0051 | 0.0326 | 0.0340 | | toilet | 0.0119 | 0.0180 | 0.0977 | | Avg. | 0.0092 | 0.0259 | 0.0956 |
0
| Class | Guptaet.al | RGB | Depth | RGB-D | | --- | --- | --- | --- | --- | | bedroom | 79 | 79.06 | 78.01 | 82.72 | | kitchen | 74 | 65.09 | 60.38 | 75.47 | | livingroom | 47 | 73.83 | 33.64 | 75.70 | | bathroom | 67 | 89.66 | 81.03 | 96.55 |
| diningroom | 47 | 96.36 | 50.91 | 96.36 | | --- | --- | --- | --- | --- | | office | 24 | 63.16 | 13.16 | 71.05 | | homeoffice | 8.3 | 70.83 | 0.00 | 62.50 | | classroom | 48 | 69.57 | 52.17 | 82.61 | | bookstore | 64 | 100.00 | 72.73 | 100.00 | | others | 15 | 85.37 | 39.02 | 95.12 | | meandiag.cm. | 47 | 79.29 | 48.11 | 83.81 | | avg.accuracy | 58 | 77.52 | 55.81 | 82.42 |
1
| Class | Guptaet.al | RGB | Depth | RGB-D | | --- | --- | --- | --- | --- | | bedroom | 79 | 79.06 | 78.01 | 82.72 | | kitchen | 74 | 65.09 | 60.38 | 75.47 | | livingroom | 47 | 73.83 | 33.64 | 75.70 | | bathroom | 67 | 89.66 | 81.03 | 96.55 |
| desk | 0.0122 | 0.0298 | 0.0731 | | --- | --- | --- | --- | | dresser | 0.0038 | 0.0384 | 0.1558 | | monitor | 0.0103 | 0.0220 | 0.0783 | | nightstand | 0.0080 | 0.0248 | 0.2925 | | sofa | 0.0068 | 0.0186 | 0.0563 | | table | 0.0051 | 0.0326 | 0.0340 | | toilet | 0.0119 | 0.0180 | 0.0977 | | Avg. | 0.0092 | 0.0259 | 0.0956 |
0
| GraphMotif | Static<br>SubgraphsTime | Ξ΄=1hour<br>SubgraphsTimeSpeedUp | | --- | --- | --- | | CollegeMSGM1<br>CollegeMSGM2<br>CollegeMSGM3<br>CollegeMSGM4<br>CollegeMSGM5<br>CollegeMSGM6 | 87618.8<br>238K43.2<br>1.57K19.3<br>482.18<br>202M9.88K<br>10.9M2.02K | 3.46K0.54634.5x<br>75.4K2.0421.1x<br>1.06K0.49938.6x<br>00.2967.38x<br>1.28M35.1281x<br>227K6.74300x | | Email-EuM1<br>Email-EuM2<br>Email-EuM3<br>Email-EuM4<br>Email-EuM5<br>Email-EuM6 | 3.96K33.5<br>367K91.4<br>12.0K40.1<br>5544.99<br>57.7M7.18K<br>7.08M1.54K | 2581.1429.4x<br>30.1K1.8050.9x<br>4931.1534.7x<br>231.094.57x<br>4.71M13154.9x<br>31.1K2.45627x | | GraphMotif | Static<br>SubgraphsTime | Ξ΄=1day<br>SubgraphsTimeSpeedUp |
| MathOverflowM1<br>MathOverflowM2<br>MathOverflowM3<br>MathOverflowM4<br>MathOverflowM5<br>MathOverflowM6 | 1.42M2.94K<br>218M11.4K<br>5.53M4.02K<br>285K2.34K<br>β€”>24hr<br>β€”>24hr | 20.0012.94Mx<br>2480.015760Kx<br>40.0014.02Mx<br>00.015156Kx<br>8050.031>2.79Mx<br>1.70K0.062>1.39Mx | | --- | --- | --- | | EnronM1<br>EnronM2<br>EnronM3<br>EnronM4<br>EnronM5<br>EnronM6 | 246K1.21K<br>119M4.51K<br>1.71M1.62K<br>33.3K55.6<br>β€”>24hr<br>β€”>24hr | 20.04626.3Kx<br>1.21K0.07857.9Kx<br>20.04734.4Kx<br>00.0471.18Kx<br>12.6M333>259x<br>2.33K0.28>309Kx |
1
| GraphMotif | Static<br>SubgraphsTime | Ξ΄=1hour<br>SubgraphsTimeSpeedUp | | --- | --- | --- | | CollegeMSGM1<br>CollegeMSGM2<br>CollegeMSGM3<br>CollegeMSGM4<br>CollegeMSGM5<br>CollegeMSGM6 | 87618.8<br>238K43.2<br>1.57K19.3<br>482.18<br>202M9.88K<br>10.9M2.02K | 3.46K0.54634.5x<br>75.4K2.0421.1x<br>1.06K0.49938.6x<br>00.2967.38x<br>1.28M35.1281x<br>227K6.74300x | | Email-EuM1<br>Email-EuM2<br>Email-EuM3<br>Email-EuM4<br>Email-EuM5<br>Email-EuM6 | 3.96K33.5<br>367K91.4<br>12.0K40.1<br>5544.99<br>57.7M7.18K<br>7.08M1.54K | 2581.1429.4x<br>30.1K1.8050.9x<br>4931.1534.7x<br>231.094.57x<br>4.71M13154.9x<br>31.1K2.45627x | | GraphMotif | Static<br>SubgraphsTime | Ξ΄=1day<br>SubgraphsTimeSpeedUp |
| Graph | Nodes<br>(Million) | Edges<br>(Million) | Outdegrees<br>MaxAvgσ | | --- | --- | --- | --- | | rmat20 | 1.05 | 8.26 | 1,1818177.40 | | road-FLA<br>road-W<br>road-USA | 1.07<br>6.26<br>23.95 | 2.71<br>15.12<br>57.71 | 832.45<br>942.74<br>932.74 | | ER20<br>ER23 | 1.05<br>8.39 | 4.19<br>33.55 | 1544.47<br>1034.46 | | Graph500<br>(threegraphs) | 16.78 | 335.00 | 924,0002020,900 |
0
| GraphMotif | Static<br>SubgraphsTime | Ξ΄=1hour<br>SubgraphsTimeSpeedUp | | --- | --- | --- | | CollegeMSGM1<br>CollegeMSGM2<br>CollegeMSGM3<br>CollegeMSGM4<br>CollegeMSGM5<br>CollegeMSGM6 | 87618.8<br>238K43.2<br>1.57K19.3<br>482.18<br>202M9.88K<br>10.9M2.02K | 3.46K0.54634.5x<br>75.4K2.0421.1x<br>1.06K0.49938.6x<br>00.2967.38x<br>1.28M35.1281x<br>227K6.74300x |
| Email-EuM1<br>Email-EuM2<br>Email-EuM3<br>Email-EuM4<br>Email-EuM5<br>Email-EuM6 | 3.96K33.5<br>367K91.4<br>12.0K40.1<br>5544.99<br>57.7M7.18K<br>7.08M1.54K | 2581.1429.4x<br>30.1K1.8050.9x<br>4931.1534.7x<br>231.094.57x<br>4.71M13154.9x<br>31.1K2.45627x | | --- | --- | --- | | GraphMotif | Static<br>SubgraphsTime | Ξ΄=1day<br>SubgraphsTimeSpeedUp | | MathOverflowM1<br>MathOverflowM2<br>MathOverflowM3<br>MathOverflowM4<br>MathOverflowM5<br>MathOverflowM6 | 1.42M2.94K<br>218M11.4K<br>5.53M4.02K<br>285K2.34K<br>β€”>24hr<br>β€”>24hr | 20.0012.94Mx<br>2480.015760Kx<br>40.0014.02Mx<br>00.015156Kx<br>8050.031>2.79Mx<br>1.70K0.062>1.39Mx | | EnronM1<br>EnronM2<br>EnronM3<br>EnronM4<br>EnronM5<br>EnronM6 | 246K1.21K<br>119M4.51K<br>1.71M1.62K<br>33.3K55.6<br>β€”>24hr<br>β€”>24hr | 20.04626.3Kx<br>1.21K0.07857.9Kx<br>20.04734.4Kx<br>00.0471.18Kx<br>12.6M333>259x<br>2.33K0.28>309Kx |
1
| GraphMotif | Static<br>SubgraphsTime | Ξ΄=1hour<br>SubgraphsTimeSpeedUp | | --- | --- | --- | | CollegeMSGM1<br>CollegeMSGM2<br>CollegeMSGM3<br>CollegeMSGM4<br>CollegeMSGM5<br>CollegeMSGM6 | 87618.8<br>238K43.2<br>1.57K19.3<br>482.18<br>202M9.88K<br>10.9M2.02K | 3.46K0.54634.5x<br>75.4K2.0421.1x<br>1.06K0.49938.6x<br>00.2967.38x<br>1.28M35.1281x<br>227K6.74300x |
| road-FLA<br>road-W<br>road-USA | 1.07<br>6.26<br>23.95 | 2.71<br>15.12<br>57.71 | 832.45<br>942.74<br>932.74 | | --- | --- | --- | --- | | ER20<br>ER23 | 1.05<br>8.39 | 4.19<br>33.55 | 1544.47<br>1034.46 | | Graph500<br>(threegraphs) | 16.78 | 335.00 | 924,0002020,900 |
0
| -classe1800(attendus=169,ramenes=102.00,corrects=6.00)<br>rappel=0.036precision=0.059f-mesure=0.044 | | --- | | -classe1810(attendus=169,ramenes=193.00,corrects=27.00)<br>rappel=0.160precision=0.140f-mesure=0.149 | | -classe1820(attendus=169,ramenes=321.00,corrects=41.00)<br>rappel=0.243precision=0.128f-mesure=0.167 | | -classe1830(attendus=169,ramenes=422.00,corrects=40.00)<br>rappel=0.237precision=0.095f-mesure=0.135 | | -classe1840(attendus=169,ramenes=83.00,corrects=9.00)<br>rappel=0.053precision=0.108f-mesure=0.071 | | -classe1850(attendus=169,ramenes=166.00,corrects=13.00)<br>rappel=0.077precision=0.078f-mesure=0.078 | | -classe1860(attendus=170,ramenes=111.00,corrects=8.00)<br>rappel=0.047precision=0.072f-mesure=0.057 | | -classe1870(attendus=169,ramenes=82.00,corrects=7.00)<br>rappel=0.041precision=0.085f-mesure=0.056 |
| -classe1880(attendus=169,ramenes=118.00,corrects=13.00)<br>rappel=0.077precision=0.110f-mesure=0.091 | | --- | | -classe1890(attendus=197,ramenes=78.00,corrects=9.00)<br>rappel=0.046precision=0.115f-mesure=0.065 | | -classe1900(attendus=203,ramenes=135.00,corrects=16.00)<br>rappel=0.079precision=0.119f-mesure=0.095 | | -classe1910(attendus=201,ramenes=67.00,corrects=6.00)<br>rappel=0.030precision=0.090f-mesure=0.045 | | -classe1920(attendus=200,ramenes=143.00,corrects=18.00)<br>rappel=0.090precision=0.126f-mesure=0.105 | | -classe1930(attendus=200,ramenes=80.00,corrects=9.00)<br>rappel=0.045precision=0.113f-mesure=0.064 | | -classe1940(attendus=198,ramenes=620.00,corrects=93.00)<br>rappel=0.470precision=0.150f-mesure=0.227 | | -surl’ensembledes15classes<br>macrorappel=0.115macroprecision=0.106macroF-mesure=0.110 |
1
| -classe1800(attendus=169,ramenes=102.00,corrects=6.00)<br>rappel=0.036precision=0.059f-mesure=0.044 | | --- | | -classe1810(attendus=169,ramenes=193.00,corrects=27.00)<br>rappel=0.160precision=0.140f-mesure=0.149 | | -classe1820(attendus=169,ramenes=321.00,corrects=41.00)<br>rappel=0.243precision=0.128f-mesure=0.167 | | -classe1830(attendus=169,ramenes=422.00,corrects=40.00)<br>rappel=0.237precision=0.095f-mesure=0.135 | | -classe1840(attendus=169,ramenes=83.00,corrects=9.00)<br>rappel=0.053precision=0.108f-mesure=0.071 | | -classe1850(attendus=169,ramenes=166.00,corrects=13.00)<br>rappel=0.077precision=0.078f-mesure=0.078 | | -classe1860(attendus=170,ramenes=111.00,corrects=8.00)<br>rappel=0.047precision=0.072f-mesure=0.057 | | -classe1870(attendus=169,ramenes=82.00,corrects=7.00)<br>rappel=0.041precision=0.085f-mesure=0.056 |
| -classe1800(attendus=169,ramenes=102.00,corrects=6.00)<br>rappel=0.036precision=0.059f-mesure=0.044 | | --- | | -classe1810(attendus=169,ramenes=193.00,corrects=27.00)<br>rappel=0.160precision=0.140f-mesure=0.149 | | -classe1820(attendus=169,ramenes=321.00,corrects=41.00)<br>rappel=0.243precision=0.128f-mesure=0.167 | | -classe1830(attendus=169,ramenes=422.00,corrects=40.00)<br>rappel=0.237precision=0.095f-mesure=0.135 | | -classe1840(attendus=169,ramenes=83.00,corrects=9.00)<br>rappel=0.053precision=0.108f-mesure=0.071 | | -classe1850(attendus=169,ramenes=166.00,corrects=13.00)<br>rappel=0.077precision=0.078f-mesure=0.078 | | -classe1860(attendus=170,ramenes=111.00,corrects=8.00)<br>rappel=0.047precision=0.072f-mesure=0.057 | | -classe1870(attendus=169,ramenes=82.00,corrects=7.00)<br>rappel=0.041precision=0.085f-mesure=0.056 | | -classe1880(attendus=169,ramenes=118.00,corrects=13.00)<br>rappel=0.077precision=0.110f-mesure=0.091 | | -classe1890(attendus=197,ramenes=78.00,corrects=9.00)<br>rappel=0.046precision=0.115f-mesure=0.065 | | -classe1900(attendus=203,ramenes=135.00,corrects=16.00)<br>rappel=0.079precision=0.119f-mesure=0.095 | | -classe1910(attendus=201,ramenes=67.00,corrects=6.00)<br>rappel=0.030precision=0.090f-mesure=0.045 | | -classe1920(attendus=200,ramenes=143.00,corrects=18.00)<br>rappel=0.090precision=0.126f-mesure=0.105 | | -classe1930(attendus=200,ramenes=80.00,corrects=9.00)<br>rappel=0.045precision=0.113f-mesure=0.064 | | -classe1940(attendus=198,ramenes=620.00,corrects=93.00)<br>rappel=0.470precision=0.150f-mesure=0.227 | | -surl’ensembledes15classes<br>macrorappel=0.115macroprecision=0.106macroF-mesure=0.110 |
0
| -classe1800(attendus=169,ramenes=102.00,corrects=6.00)<br>rappel=0.036precision=0.059f-mesure=0.044 | | --- | | -classe1810(attendus=169,ramenes=193.00,corrects=27.00)<br>rappel=0.160precision=0.140f-mesure=0.149 | | -classe1820(attendus=169,ramenes=321.00,corrects=41.00)<br>rappel=0.243precision=0.128f-mesure=0.167 | | -classe1830(attendus=169,ramenes=422.00,corrects=40.00)<br>rappel=0.237precision=0.095f-mesure=0.135 | | -classe1840(attendus=169,ramenes=83.00,corrects=9.00)<br>rappel=0.053precision=0.108f-mesure=0.071 | | -classe1850(attendus=169,ramenes=166.00,corrects=13.00)<br>rappel=0.077precision=0.078f-mesure=0.078 | | -classe1860(attendus=170,ramenes=111.00,corrects=8.00)<br>rappel=0.047precision=0.072f-mesure=0.057 | | -classe1870(attendus=169,ramenes=82.00,corrects=7.00)<br>rappel=0.041precision=0.085f-mesure=0.056 | | -classe1880(attendus=169,ramenes=118.00,corrects=13.00)<br>rappel=0.077precision=0.110f-mesure=0.091 | | -classe1890(attendus=197,ramenes=78.00,corrects=9.00)<br>rappel=0.046precision=0.115f-mesure=0.065 |
| -classe1900(attendus=203,ramenes=135.00,corrects=16.00)<br>rappel=0.079precision=0.119f-mesure=0.095 | | --- | | -classe1910(attendus=201,ramenes=67.00,corrects=6.00)<br>rappel=0.030precision=0.090f-mesure=0.045 | | -classe1920(attendus=200,ramenes=143.00,corrects=18.00)<br>rappel=0.090precision=0.126f-mesure=0.105 | | -classe1930(attendus=200,ramenes=80.00,corrects=9.00)<br>rappel=0.045precision=0.113f-mesure=0.064 | | -classe1940(attendus=198,ramenes=620.00,corrects=93.00)<br>rappel=0.470precision=0.150f-mesure=0.227 | | -surl’ensembledes15classes<br>macrorappel=0.115macroprecision=0.106macroF-mesure=0.110 |
1
| -classe1800(attendus=169,ramenes=102.00,corrects=6.00)<br>rappel=0.036precision=0.059f-mesure=0.044 | | --- | | -classe1810(attendus=169,ramenes=193.00,corrects=27.00)<br>rappel=0.160precision=0.140f-mesure=0.149 | | -classe1820(attendus=169,ramenes=321.00,corrects=41.00)<br>rappel=0.243precision=0.128f-mesure=0.167 | | -classe1830(attendus=169,ramenes=422.00,corrects=40.00)<br>rappel=0.237precision=0.095f-mesure=0.135 | | -classe1840(attendus=169,ramenes=83.00,corrects=9.00)<br>rappel=0.053precision=0.108f-mesure=0.071 | | -classe1850(attendus=169,ramenes=166.00,corrects=13.00)<br>rappel=0.077precision=0.078f-mesure=0.078 | | -classe1860(attendus=170,ramenes=111.00,corrects=8.00)<br>rappel=0.047precision=0.072f-mesure=0.057 | | -classe1870(attendus=169,ramenes=82.00,corrects=7.00)<br>rappel=0.041precision=0.085f-mesure=0.056 | | -classe1880(attendus=169,ramenes=118.00,corrects=13.00)<br>rappel=0.077precision=0.110f-mesure=0.091 | | -classe1890(attendus=197,ramenes=78.00,corrects=9.00)<br>rappel=0.046precision=0.115f-mesure=0.065 |
| -classe1900(attendus=203,ramenes=135.00,corrects=16.00)<br>rappel=0.079precision=0.119f-mesure=0.095 | | --- | | -classe1910(attendus=201,ramenes=67.00,corrects=6.00)<br>rappel=0.030precision=0.090f-mesure=0.045 | | -classe1920(attendus=200,ramenes=143.00,corrects=18.00)<br>rappel=0.090precision=0.126f-mesure=0.105 | | -classe1930(attendus=200,ramenes=80.00,corrects=9.00)<br>rappel=0.045precision=0.113f-mesure=0.064 | | -classe1940(attendus=198,ramenes=620.00,corrects=93.00)<br>rappel=0.470precision=0.150f-mesure=0.227 | | -surl’ensembledes15classes<br>macrorappel=0.115macroprecision=0.106macroF-mesure=0.110 |
0
| Algorithms | Memory(MB) | | --- | --- | | VGG | 2459.8 | | SSDGoogleNet | 320.4 |
| SqueezeNet | 145.3 | | --- | --- | | MobileNet | 172.2 | | L-CNN | 139.5 |
1
| Algorithms | Memory(MB) | | --- | --- | | VGG | 2459.8 | | SSDGoogleNet | 320.4 |
| CNN | Imageresolution | RunTime(ms) | | --- | --- | --- | | AlexNet | 227Γ—227 | 2.3 | | VGG16 | 224Γ—224 | 10 | | Resnet50 | 224Γ—224 | 17 | | SqueezeNet | 224Γ—224 | 2.5 | | SqueezeNet | 448Γ—448 | 4 | | SqueezeNet | 625Γ—625 | 6 |
0
| Algorithms | Memory(MB) | | --- | --- | | VGG | 2459.8 |
| SSDGoogleNet | 320.4 | | --- | --- | | SqueezeNet | 145.3 | | MobileNet | 172.2 | | L-CNN | 139.5 |
1
| Algorithms | Memory(MB) | | --- | --- | | VGG | 2459.8 |
| SqueezeNet | 224Γ—224 | 2.5 | | --- | --- | --- | | SqueezeNet | 448Γ—448 | 4 | | SqueezeNet | 625Γ—625 | 6 |
0
| | SDR(dB) | SIR(dB) | SAR(dB) | | | | | --- | --- | --- | --- | --- | --- | --- | | | MDLD | GaussSep | MDLD | GaussSep | MDLD | GaussSep |
| Dev3Female3 | 6.02 | 16.93 | 23.84 | 22.43 | 6.17 | 18.40 | | --- | --- | --- | --- | --- | --- | --- | | Example3Γ—5 | 3.91 | 9.94 | 17.92 | 15.21 | 4.17 | 11.68 | | Example4Γ—8 | 2.24 | -18.63 | 16.4 | -17.58 | 2.52 | 9.39 |
1
| | SDR(dB) | SIR(dB) | SAR(dB) | | | | | --- | --- | --- | --- | --- | --- | --- | | | MDLD | GaussSep | MDLD | GaussSep | MDLD | GaussSep |
| | SDR(dB) | SIR(dB) | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | WMDLD | MDLD | GS | WMDLD | MDLD | GS | WMDLD | MDLD | | Dev3Female4 | 11.77 | 6.02 | 16.93 | 22.26 | 23.84 | 22.43 | 12.23 | 6.17 | | Example3Γ—5 | 8.41 | 3.91 | 9.94 | 17.58 | 17.92 | 15.21 | 9.10 | 4.17 | | Example4Γ—8 | 5.29 | 2.24 | -18.63 | 13.72 | 16.4 | -17.58 | 6.23 | 2.52 |
0
| | SDR(dB) | SIR(dB) | SAR(dB) | | | | | --- | --- | --- | --- | --- | --- | --- | | | MDLD | GaussSep | MDLD | GaussSep | MDLD | GaussSep |
| Dev3Female3 | 6.02 | 16.93 | 23.84 | 22.43 | 6.17 | 18.40 | | --- | --- | --- | --- | --- | --- | --- | | Example3Γ—5 | 3.91 | 9.94 | 17.92 | 15.21 | 4.17 | 11.68 | | Example4Γ—8 | 2.24 | -18.63 | 16.4 | -17.58 | 2.52 | 9.39 |
1
| | SDR(dB) | SIR(dB) | SAR(dB) | | | | | --- | --- | --- | --- | --- | --- | --- | | | MDLD | GaussSep | MDLD | GaussSep | MDLD | GaussSep |
| Example3Γ—5 | 8.41 | 3.91 | 9.94 | 17.58 | 17.92 | 15.21 | 9.10 | 4.17 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Example4Γ—8 | 5.29 | 2.24 | -18.63 | 13.72 | 16.4 | -17.58 | 6.23 | 2.52 |
0
| UL<br>GN | | --- | | UL<br>GN | | UL<br>GN |
| UL<br>GN | | --- | | UL<br>GN |
1
| UL<br>GN | | --- | | UL<br>GN | | UL<br>GN |
| | | --- | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL |
0
| UL<br>GN | | --- | | UL<br>GN | | UL<br>GN |
| UL<br>GN | | --- | | UL<br>GN |
1
| UL<br>GN | | --- | | UL<br>GN | | UL<br>GN |
| SL<br>DRL | | --- | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL | | SL<br>DRL |
0
| Class(Tissuetype) | T<br>Labely | | --- | --- | | class1(BK) | (1,0,0,0,0) |
| class2(LP) | (0,1,0,0,0) | | --- | --- | | class3(FT) | (0,0,1,0,0) | | class4(MT) | (0,0,0,1,0) | | class5(CA) | (0,0,0,0,1) |
1
| Class(Tissuetype) | T<br>Labely | | --- | --- | | class1(BK) | (1,0,0,0,0) |
| TypeofLesion | Class | | --- | --- | | Healthy/NoLesionandBackground | 0 | | NecroticRegion | 1 | | Edema | 2 | | NonEnhancingTumor | 3 | | EnhancingTumor | 4 |
0
| Class(Tissuetype) | T<br>Labely | | --- | --- | | class1(BK) | (1,0,0,0,0) | | class2(LP) | (0,1,0,0,0) | | class3(FT) | (0,0,1,0,0) |
| class4(MT) | (0,0,0,1,0) | | --- | --- | | class5(CA) | (0,0,0,0,1) |
1
| Class(Tissuetype) | T<br>Labely | | --- | --- | | class1(BK) | (1,0,0,0,0) | | class2(LP) | (0,1,0,0,0) | | class3(FT) | (0,0,1,0,0) |
| NonEnhancingTumor | 3 | | --- | --- | | EnhancingTumor | 4 |
0
| | SubgamePerfect<br>Equilibrium | PerfectPrediction<br>Equilibrium | | --- | --- | --- | | FormoftheGame | Extensive | Extensive | | PerfectInformation | Yes | Yes | | Numberofplayers | Any | Any | | NewcombChoice | Twoboxes | Onebox | | PredictionModel<br>accountingfor<br>counterfactuals | Ad-HocPrediction<br>(β€œcouldhave<br>beenwrong”) | PerfectPrediction<br>(β€œwouldalso<br>havebeenright”) | | RelationshipwiththePast | Cournot-like | Stackelberg-like | | Reasoning | BackwardInduction | ForwardInduction | | Indifferencebetweenpayoffs | Allowed | Notallowedinprinciple |
| Existence | Always | Always | | --- | --- | --- | | Uniqueness | Always | Always | | Optimality | - | Pareto | | Corresponding<br>NormalForm | Nash<br>(subsuming) | Superrationality(notestablished/<br>conceptuallysimilar) |
1
| | SubgamePerfect<br>Equilibrium | PerfectPrediction<br>Equilibrium | | --- | --- | --- | | FormoftheGame | Extensive | Extensive | | PerfectInformation | Yes | Yes | | Numberofplayers | Any | Any | | NewcombChoice | Twoboxes | Onebox | | PredictionModel<br>accountingfor<br>counterfactuals | Ad-HocPrediction<br>(β€œcouldhave<br>beenwrong”) | PerfectPrediction<br>(β€œwouldalso<br>havebeenright”) | | RelationshipwiththePast | Cournot-like | Stackelberg-like | | Reasoning | BackwardInduction | ForwardInduction | | Indifferencebetweenpayoffs | Allowed | Notallowedinprinciple |
| Criterion | MANCaLog | IC/LT | SNOP | CD | EGT/VM | | --- | --- | --- | --- | --- | --- | | 1.Labels | Yes | No | Yes | Yes | No | | 2.ExplicitRepresentationofTime | Yes | No | Yes | No | Yes | | 3.Non-MarkovianTemporalRelationships | Yes | No | No | No | No | | 4.Uncertainty | Yes | Yes | Yes | Yes | Yes | | 5.CompetingCascades | Yes | No | No | Yes | Yes | | 6.Non-monotonicCascades | Yes | No | No | Yes | Yes | | 7.Tractablity | PTIME | #P-hard | PTIME | PTIME | NP-hard |
0
| | SubgamePerfect<br>Equilibrium | PerfectPrediction<br>Equilibrium | | --- | --- | --- | | FormoftheGame | Extensive | Extensive | | PerfectInformation | Yes | Yes | | Numberofplayers | Any | Any | | NewcombChoice | Twoboxes | Onebox | | PredictionModel<br>accountingfor<br>counterfactuals | Ad-HocPrediction<br>(β€œcouldhave<br>beenwrong”) | PerfectPrediction<br>(β€œwouldalso<br>havebeenright”) | | RelationshipwiththePast | Cournot-like | Stackelberg-like | | Reasoning | BackwardInduction | ForwardInduction | | Indifferencebetweenpayoffs | Allowed | Notallowedinprinciple | | Existence | Always | Always |
| Uniqueness | Always | Always | | --- | --- | --- | | Optimality | - | Pareto | | Corresponding<br>NormalForm | Nash<br>(subsuming) | Superrationality(notestablished/<br>conceptuallysimilar) |
1
| | SubgamePerfect<br>Equilibrium | PerfectPrediction<br>Equilibrium | | --- | --- | --- | | FormoftheGame | Extensive | Extensive | | PerfectInformation | Yes | Yes | | Numberofplayers | Any | Any | | NewcombChoice | Twoboxes | Onebox | | PredictionModel<br>accountingfor<br>counterfactuals | Ad-HocPrediction<br>(β€œcouldhave<br>beenwrong”) | PerfectPrediction<br>(β€œwouldalso<br>havebeenright”) | | RelationshipwiththePast | Cournot-like | Stackelberg-like | | Reasoning | BackwardInduction | ForwardInduction | | Indifferencebetweenpayoffs | Allowed | Notallowedinprinciple | | Existence | Always | Always |
| 2.ExplicitRepresentationofTime | Yes | No | Yes | No | Yes | | --- | --- | --- | --- | --- | --- | | 3.Non-MarkovianTemporalRelationships | Yes | No | No | No | No | | 4.Uncertainty | Yes | Yes | Yes | Yes | Yes | | 5.CompetingCascades | Yes | No | No | Yes | Yes | | 6.Non-monotonicCascades | Yes | No | No | Yes | Yes | | 7.Tractablity | PTIME | #P-hard | PTIME | PTIME | NP-hard |
0
| category | ours | | | | --- | --- | --- | --- | | bathtub | 0.0152 | 0.0266 | 0.0621 | | bed | 0.0068 | 0.0240 | 0.0617 |
| chair | 0.0118 | 0.0238 | 0.0444 | | --- | --- | --- | --- | | desk | 0.0122 | 0.0298 | 0.0731 | | dresser | 0.0038 | 0.0384 | 0.1558 | | monitor | 0.0103 | 0.0220 | 0.0783 | | nightstand | 0.0080 | 0.0248 | 0.2925 | | sofa | 0.0068 | 0.0186 | 0.0563 | | table | 0.0051 | 0.0326 | 0.0340 | | toilet | 0.0119 | 0.0180 | 0.0977 | | Avg. | 0.0092 | 0.0259 | 0.0956 |
1
| category | ours | | | | --- | --- | --- | --- | | bathtub | 0.0152 | 0.0266 | 0.0621 | | bed | 0.0068 | 0.0240 | 0.0617 |
| category | ours | | | | | --- | --- | --- | --- | --- | | bathtub | 0.8348 | 0.7017 | 0.7190 | 0.1644 | | bed | 0.9202 | 0.7775 | 0.3963 | 0.3239 | | chair | 0.9920 | 0.9700 | 0.9892 | 0.8482 | | desk | 0.8203 | 0.7936 | 0.8145 | 0.1068 | | dresser | 0.7678 | 0.6314 | 0.7010 | 0.2166 | | monitor | 0.9473 | 0.2493 | 0.8559 | 0.2767 | | nightstand | 0.7195 | 0.6853 | 0.6592 | 0.4969 | | sofa | 0.9480 | 0.9276 | 0.3017 | 0.4888 | | table | 0.8910 | 0.8377 | 0.8751 | 0.7902 | | toilet | 0.9701 | 0.8569 | 0.6943 | 0.8832 | | Avg. | 0.8811 | 0.7431 | 0.7006 | 0.4596 |
0
| category | ours | | | | --- | --- | --- | --- | | bathtub | 0.0152 | 0.0266 | 0.0621 | | bed | 0.0068 | 0.0240 | 0.0617 | | chair | 0.0118 | 0.0238 | 0.0444 | | desk | 0.0122 | 0.0298 | 0.0731 | | dresser | 0.0038 | 0.0384 | 0.1558 | | monitor | 0.0103 | 0.0220 | 0.0783 |
| nightstand | 0.0080 | 0.0248 | 0.2925 | | --- | --- | --- | --- | | sofa | 0.0068 | 0.0186 | 0.0563 | | table | 0.0051 | 0.0326 | 0.0340 | | toilet | 0.0119 | 0.0180 | 0.0977 | | Avg. | 0.0092 | 0.0259 | 0.0956 |
1
| category | ours | | | | --- | --- | --- | --- | | bathtub | 0.0152 | 0.0266 | 0.0621 | | bed | 0.0068 | 0.0240 | 0.0617 | | chair | 0.0118 | 0.0238 | 0.0444 | | desk | 0.0122 | 0.0298 | 0.0731 | | dresser | 0.0038 | 0.0384 | 0.1558 | | monitor | 0.0103 | 0.0220 | 0.0783 |
| table | 0.8910 | 0.8377 | 0.8751 | 0.7902 | | --- | --- | --- | --- | --- | | toilet | 0.9701 | 0.8569 | 0.6943 | 0.8832 | | Avg. | 0.8811 | 0.7431 | 0.7006 | 0.4596 |
0
| Facet | Numberofmanually<br>definedclusters | Hierarchicalclustering | Non-hierarchicalclustering | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | Purity | I-Purity | F1 | Purity | I-Purity | F1 | | | | Battery | 4 | 0.864 | 0.591 | 0.702 | 0.864 | 0.636 | 0.733 | | Memory | 3 | 0.643 | 1.000 | 0.783 | 0.643 | 0.786 | 0.707 | | Flash | 4 | 0.556 | 0.722 | 0.628 | 0.667 | 0.722 | 0.693 | | LCD | 6 | 0.478 | 0.826 | 0.606 | 0.565 | 1.000 | 0.722 | | Lens | 7 | 0.792 | 1.000 | 0.884 | 0.792 | 1.000 | 0.884 | | Megapixels | 5 | 0.621 | 0.483 | 0.543 | 0.724 | 0.552 | 0.626 | | Mode | 6 | 0.813 | 1.000 | 0.897 | 0.813 | 1.000 | 0.897 |
| Shutter | 6 | 0.643 | 0.929 | 0.760 | 0.643 | 0.929 | 0.760 | | --- | --- | --- | --- | --- | --- | --- | --- | | Average | 5.13 | 0.676 | 0.819 | 0.725 | 0.714 | 0.828 | 0.753 | | Battery | 3 | 0.824 | 0.765 | 0.793 | 0.765 | 0.706 | 0.734 | | Camera | 3 | 0.727 | 0.636 | 0.679 | 0.727 | 0.636 | 0.679 | | Headset | 4 | 0.467 | 0.733 | 0.570 | 0.400 | 0.600 | 0.480 | | Radio | 3 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | | Service | 5 | 0.438 | 0.875 | 0.583 | 0.563 | 1.000 | 0.720 | | Signal | 3 | 0.824 | 0.941 | 0.878 | 0.824 | 0.765 | 0.793 | | Size | 3 | 0.760 | 0.680 | 0.718 | 0.920 | 0.680 | 0.782 | | Speaker | 4 | 0.684 | 0.895 | 0.775 | 0.684 | 0.789 | 0.733 | | Average | 3.50 | 0.682 | 0.783 | 0.717 | 0.702 | 0.739 | 0.722 | | Price | 1 | 1.000 | 0.714 | 0.833 | 1.000 | 0.762 | 0.865 | | Remote | 4 | 0.625 | 0.750 | 0.682 | 0.563 | 0.750 | 0.643 | | Format | 1 | 1.000 | 0.714 | 0.833 | 1.000 | 0.571 | 0.727 | | Design | 1 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | | Service | 1 | 1.000 | 0.739 | 0.850 | 1.000 | 0.522 | 0.686 | | Picture | 4 | 0.800 | 0.850 | 0.824 | 0.800 | 0.850 | 0.824 | | Average | 2.00 | 0.904 | 0.795 | 0.837 | 0.894 | 0.743 | 0.791 |
1
| Facet | Numberofmanually<br>definedclusters | Hierarchicalclustering | Non-hierarchicalclustering | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | Purity | I-Purity | F1 | Purity | I-Purity | F1 | | | | Battery | 4 | 0.864 | 0.591 | 0.702 | 0.864 | 0.636 | 0.733 | | Memory | 3 | 0.643 | 1.000 | 0.783 | 0.643 | 0.786 | 0.707 | | Flash | 4 | 0.556 | 0.722 | 0.628 | 0.667 | 0.722 | 0.693 | | LCD | 6 | 0.478 | 0.826 | 0.606 | 0.565 | 1.000 | 0.722 | | Lens | 7 | 0.792 | 1.000 | 0.884 | 0.792 | 1.000 | 0.884 | | Megapixels | 5 | 0.621 | 0.483 | 0.543 | 0.724 | 0.552 | 0.626 | | Mode | 6 | 0.813 | 1.000 | 0.897 | 0.813 | 1.000 | 0.897 |
| | 5VirtualLandscapeDatasets | 7VirtualLandscapeDatasets | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | N-based | G-based | I-based | N-based | G-based | I-based | N-based | | | Accuracy | 0.9931 | 0.9950 | 0.9927 | 0.9939 | 0.9950 | 0.9930 | 0.9936 | | Precision | 0.6154 | 0.7080 | 0.7143 | 0.5820 | 0.7080 | 0.7590 | 0.6939 | | Recall | 0.5161 | 0.6452 | 0.4839 | 0.5726 | 0.6452 | 0.5081 | 0.5484 | | F-measure | 0.5614 | 0.6751 | 0.5769 | 0.5772 | 0.6751 | 0.6087 | 0.6126 | | R.T(second) | 2.74 | 2.67 | 2.41 | 3.29 | 3.30 | 3.44 | 4.69 | | M.U(MB) | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 |
0
| Facet | Numberofmanually<br>definedclusters | Hierarchicalclustering | Non-hierarchicalclustering | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | Purity | I-Purity | F1 | Purity | I-Purity | F1 | | | | Battery | 4 | 0.864 | 0.591 | 0.702 | 0.864 | 0.636 | 0.733 | | Memory | 3 | 0.643 | 1.000 | 0.783 | 0.643 | 0.786 | 0.707 | | Flash | 4 | 0.556 | 0.722 | 0.628 | 0.667 | 0.722 | 0.693 | | LCD | 6 | 0.478 | 0.826 | 0.606 | 0.565 | 1.000 | 0.722 | | Lens | 7 | 0.792 | 1.000 | 0.884 | 0.792 | 1.000 | 0.884 | | Megapixels | 5 | 0.621 | 0.483 | 0.543 | 0.724 | 0.552 | 0.626 | | Mode | 6 | 0.813 | 1.000 | 0.897 | 0.813 | 1.000 | 0.897 | | Shutter | 6 | 0.643 | 0.929 | 0.760 | 0.643 | 0.929 | 0.760 | | Average | 5.13 | 0.676 | 0.819 | 0.725 | 0.714 | 0.828 | 0.753 | | Battery | 3 | 0.824 | 0.765 | 0.793 | 0.765 | 0.706 | 0.734 | | Camera | 3 | 0.727 | 0.636 | 0.679 | 0.727 | 0.636 | 0.679 | | Headset | 4 | 0.467 | 0.733 | 0.570 | 0.400 | 0.600 | 0.480 | | Radio | 3 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | | Service | 5 | 0.438 | 0.875 | 0.583 | 0.563 | 1.000 | 0.720 | | Signal | 3 | 0.824 | 0.941 | 0.878 | 0.824 | 0.765 | 0.793 | | Size | 3 | 0.760 | 0.680 | 0.718 | 0.920 | 0.680 | 0.782 | | Speaker | 4 | 0.684 | 0.895 | 0.775 | 0.684 | 0.789 | 0.733 | | Average | 3.50 | 0.682 | 0.783 | 0.717 | 0.702 | 0.739 | 0.722 | | Price | 1 | 1.000 | 0.714 | 0.833 | 1.000 | 0.762 | 0.865 | | Remote | 4 | 0.625 | 0.750 | 0.682 | 0.563 | 0.750 | 0.643 |
| Format | 1 | 1.000 | 0.714 | 0.833 | 1.000 | 0.571 | 0.727 | | --- | --- | --- | --- | --- | --- | --- | --- | | Design | 1 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | | Service | 1 | 1.000 | 0.739 | 0.850 | 1.000 | 0.522 | 0.686 | | Picture | 4 | 0.800 | 0.850 | 0.824 | 0.800 | 0.850 | 0.824 | | Average | 2.00 | 0.904 | 0.795 | 0.837 | 0.894 | 0.743 | 0.791 |
1
| Facet | Numberofmanually<br>definedclusters | Hierarchicalclustering | Non-hierarchicalclustering | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | Purity | I-Purity | F1 | Purity | I-Purity | F1 | | | | Battery | 4 | 0.864 | 0.591 | 0.702 | 0.864 | 0.636 | 0.733 | | Memory | 3 | 0.643 | 1.000 | 0.783 | 0.643 | 0.786 | 0.707 | | Flash | 4 | 0.556 | 0.722 | 0.628 | 0.667 | 0.722 | 0.693 | | LCD | 6 | 0.478 | 0.826 | 0.606 | 0.565 | 1.000 | 0.722 | | Lens | 7 | 0.792 | 1.000 | 0.884 | 0.792 | 1.000 | 0.884 | | Megapixels | 5 | 0.621 | 0.483 | 0.543 | 0.724 | 0.552 | 0.626 | | Mode | 6 | 0.813 | 1.000 | 0.897 | 0.813 | 1.000 | 0.897 | | Shutter | 6 | 0.643 | 0.929 | 0.760 | 0.643 | 0.929 | 0.760 | | Average | 5.13 | 0.676 | 0.819 | 0.725 | 0.714 | 0.828 | 0.753 | | Battery | 3 | 0.824 | 0.765 | 0.793 | 0.765 | 0.706 | 0.734 | | Camera | 3 | 0.727 | 0.636 | 0.679 | 0.727 | 0.636 | 0.679 | | Headset | 4 | 0.467 | 0.733 | 0.570 | 0.400 | 0.600 | 0.480 | | Radio | 3 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | 0.737 | | Service | 5 | 0.438 | 0.875 | 0.583 | 0.563 | 1.000 | 0.720 | | Signal | 3 | 0.824 | 0.941 | 0.878 | 0.824 | 0.765 | 0.793 | | Size | 3 | 0.760 | 0.680 | 0.718 | 0.920 | 0.680 | 0.782 | | Speaker | 4 | 0.684 | 0.895 | 0.775 | 0.684 | 0.789 | 0.733 | | Average | 3.50 | 0.682 | 0.783 | 0.717 | 0.702 | 0.739 | 0.722 | | Price | 1 | 1.000 | 0.714 | 0.833 | 1.000 | 0.762 | 0.865 | | Remote | 4 | 0.625 | 0.750 | 0.682 | 0.563 | 0.750 | 0.643 |
| R.T(second) | 2.74 | 2.67 | 2.41 | 3.29 | 3.30 | 3.44 | 4.69 | | --- | --- | --- | --- | --- | --- | --- | --- | | M.U(MB) | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 | 0.42 |
0
| Method | #ofHiddenLayers | #ofHiddenUnits | | --- | --- | --- | | 1DVector | One | 200;400;600;800;1000 |
| Two | [200,200];[400,400];[600,600];[800,800] | | | --- | --- | --- | | 2DConvolving | One | 144;169;196;255;256;289 | | Two | [361,100] | |
1
| Method | #ofHiddenLayers | #ofHiddenUnits | | --- | --- | --- | | 1DVector | One | 200;400;600;800;1000 |
| 2DConvolutional(filters=64,kernelsize=3,activation=”relu”,padding=”same”) | | --- | | 2DConvolutional(filters=64,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=64,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=128,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=128,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=128,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=256,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=256,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=256,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | Dense(1024,activation=β€œrelu”) | | Dropout(0.5) | | Dense(512,activation=β€œrelu”) | | Dropout(0.5) | | Dense(1,activation=None) |
0
| Method | #ofHiddenLayers | #ofHiddenUnits | | --- | --- | --- | | 1DVector | One | 200;400;600;800;1000 |
| Two | [200,200];[400,400];[600,600];[800,800] | | | --- | --- | --- | | 2DConvolving | One | 144;169;196;255;256;289 | | Two | [361,100] | |
1
| Method | #ofHiddenLayers | #ofHiddenUnits | | --- | --- | --- | | 1DVector | One | 200;400;600;800;1000 |
| 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | --- | | 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | 2DConvolutional(filters=512,kernelsize=3,activation=β€œrelu”,padding=β€œsame”) | | MaxPooling(poolsize=(2,2),strides=(2,2)) | | Dense(1024,activation=β€œrelu”) | | Dropout(0.5) | | Dense(512,activation=β€œrelu”) | | Dropout(0.5) | | Dense(1,activation=None) |
0
| Dataset | WSim(SIM) | WSim(REL) | | | | --- | --- | --- | --- | --- | | Window | 2 | 3 | 2 | 3 | | CosFreq | 0.208 | 0.158 | 0.167 | 0.175 | | CosLMI | 0.416 | 0.395 | 0.251 | 0.269 | | CosPPMI | 0.52 | 0.496 | 0.378 | 0.396 | | CosSVD-Freq300 | 0.240 | 0.214 | 0.051 | 0.084 | | CosSVD-LMI300 | 0.418 | 0.393 | 0.141 | 0.151 | | CosSVD-PPMI300 | 0.550 | 0.522 | 0.325 | 0.323 |
| APSynLMI-1000 | 0.32 | 0.29 | 0.259 | 0.241 | | --- | --- | --- | --- | --- | | APSynLMI-500 | 0.355 | 0.319 | 0.261 | 0.284 | | APSynLMI-100 | 0.388 | 0.335 | 0.233 | 0.27 | | APSynPPMI-1000 | 0.519 | 0.525 | 0.337 | 0.397 | | APSynPPMI-500 | 0.564 | 0.546 | 0.361 | 0.382 | | PMIAPSynPPMI-100 | 0.562 | 0.553 | 0.287 | 0.309 |
1
| Dataset | WSim(SIM) | WSim(REL) | | | | --- | --- | --- | --- | --- | | Window | 2 | 3 | 2 | 3 | | CosFreq | 0.208 | 0.158 | 0.167 | 0.175 | | CosLMI | 0.416 | 0.395 | 0.251 | 0.269 | | CosPPMI | 0.52 | 0.496 | 0.378 | 0.396 | | CosSVD-Freq300 | 0.240 | 0.214 | 0.051 | 0.084 | | CosSVD-LMI300 | 0.418 | 0.393 | 0.141 | 0.151 | | CosSVD-PPMI300 | 0.550 | 0.522 | 0.325 | 0.323 |
| Dataset | WSim(SIM) | WSim(REL) | | | | --- | --- | --- | --- | --- | | Window | 2 | 3 | 2 | 3 | | CosFreq | 0.335 | 0.334 | 0.03 | 0.05 | | CosLMI | 0.638 | 0.663 | 0.293 | 0.34 | | CosPPMI | 0.672 | 0.675 | 0.441 | 0.446 | | CosSVD-Freq300 | 0.35 | 0.363 | -0.013 | 0.001 | | CosSVD-LMI300 | 0.604 | 0.626 | 0.222 | 0.286 | | CosSVD-PPMI300 | 0.72 | 0.725 | 0.444 | 0.486 | | APSynLMI-1000 | 0.609 | 0.609 | 0.317 | 0.36 | | APSynLMI-500 | 0.599 | 0.601 | 0.289 | 0.344 | | APSynLMI-100 | 0.566 | 0.574 | 0.215 | 0.271 | | APSynPPMI-1000 | 0.692 | 0.726 | 0.507 | 0.568 | | APSynPPMI-500 | 0.699 | 0.742 | 0.508 | 0.571 | | APSynPPMI-100 | 0.66 | 0.692 | 0.482 | 0.516 |
0
| Dataset | WSim(SIM) | WSim(REL) | | | | --- | --- | --- | --- | --- | | Window | 2 | 3 | 2 | 3 | | CosFreq | 0.208 | 0.158 | 0.167 | 0.175 |
| CosLMI | 0.416 | 0.395 | 0.251 | 0.269 | | --- | --- | --- | --- | --- | | CosPPMI | 0.52 | 0.496 | 0.378 | 0.396 | | CosSVD-Freq300 | 0.240 | 0.214 | 0.051 | 0.084 | | CosSVD-LMI300 | 0.418 | 0.393 | 0.141 | 0.151 | | CosSVD-PPMI300 | 0.550 | 0.522 | 0.325 | 0.323 | | APSynLMI-1000 | 0.32 | 0.29 | 0.259 | 0.241 | | APSynLMI-500 | 0.355 | 0.319 | 0.261 | 0.284 | | APSynLMI-100 | 0.388 | 0.335 | 0.233 | 0.27 | | APSynPPMI-1000 | 0.519 | 0.525 | 0.337 | 0.397 | | APSynPPMI-500 | 0.564 | 0.546 | 0.361 | 0.382 | | PMIAPSynPPMI-100 | 0.562 | 0.553 | 0.287 | 0.309 |
1
| Dataset | WSim(SIM) | WSim(REL) | | | | --- | --- | --- | --- | --- | | Window | 2 | 3 | 2 | 3 | | CosFreq | 0.208 | 0.158 | 0.167 | 0.175 |
| APSynLMI-1000 | 0.609 | 0.609 | 0.317 | 0.36 | | --- | --- | --- | --- | --- | | APSynLMI-500 | 0.599 | 0.601 | 0.289 | 0.344 | | APSynLMI-100 | 0.566 | 0.574 | 0.215 | 0.271 | | APSynPPMI-1000 | 0.692 | 0.726 | 0.507 | 0.568 | | APSynPPMI-500 | 0.699 | 0.742 | 0.508 | 0.571 | | APSynPPMI-100 | 0.66 | 0.692 | 0.482 | 0.516 |
0
| Non-EnglishorMath | Frequency | Comments | | --- | --- | --- | | Ø | 1in1,000 | ForSwedishnames | | Ο€ | 1in5 | Commoninmath |
| $ | 4in5 | Usedinbusiness | | --- | --- | --- | | Ξ¨ | 1in40,000 | Unexplainedusage |
1
| Non-EnglishorMath | Frequency | Comments | | --- | --- | --- | | Ø | 1in1,000 | ForSwedishnames | | Ο€ | 1in5 | Commoninmath |
| Non-EnglishorMath | Frequency | Comments | | --- | --- | --- | | Ø | 1in1,000 | ForSwedishnames | | Ο€ | 1in5 | Commoninmath | | $ | 4in5 | Usedinbusiness | | Ξ¨ | 1in40,000 | Unexplainedusage |
0
| Non-EnglishorMath | Frequency | Comments | | --- | --- | --- | | Ø | 1in1,000 | ForSwedishnames | | Ο€ | 1in5 | Commoninmath |
| $ | 4in5 | Usedinbusiness | | --- | --- | --- | | Ξ¨ | 1in40,000 | Unexplainedusage |
1
| Non-EnglishorMath | Frequency | Comments | | --- | --- | --- | | Ø | 1in1,000 | ForSwedishnames | | Ο€ | 1in5 | Commoninmath |
| Ο€ | 1in5 | Commoninmath | | --- | --- | --- | | $ | 4in5 | Usedinbusiness | | Ξ¨ | 1in40,000 | Unexplainedusage |
0
| | 30dB | 20dB | 10dB | | --- | --- | --- | --- | | DNN-ILD | 3.03Β±.046 | 3.03Β±.046 | 3.05Β±.046 | | Linear-ILD | 2.31Β±.036 | 2.32Β±.036 | 2.36Β±.037 |
| DNN-IPD | 0.48Β±.009 | 0.48Β±.009 | 0.48Β±.009 | | --- | --- | --- | --- | | Linear-IPD | 0.40Β±.008 | 0.40Β±.008 | 0.41Β±.008 |
1
| | 30dB | 20dB | 10dB | | --- | --- | --- | --- | | DNN-ILD | 3.03Β±.046 | 3.03Β±.046 | 3.05Β±.046 | | Linear-ILD | 2.31Β±.036 | 2.32Β±.036 | 2.36Β±.037 |
| | 1cm | 2cm | 4cm | 8cm | | --- | --- | --- | --- | --- | | DNN-ILD | 3.01Β±.044 | 3.03Β±.046 | 3.10Β±.047 | 3.23Β±.049 | | Linear-ILD | 0.92Β±.017 | 2.21Β±.036 | 3.18Β±.049 | 3.43Β±.052 | | DNN-IPD | 0.46Β±.008 | 0.48Β±.009 | 0.50Β±.009 | 0.54Β±.009 | | Linear-IPD | 0.17Β±.005 | 0.38Β±.008 | 0.53Β±.009 | 0.57Β±.010 |
0
| | 30dB | 20dB | 10dB | | --- | --- | --- | --- | | DNN-ILD | 3.03Β±.046 | 3.03Β±.046 | 3.05Β±.046 | | Linear-ILD | 2.31Β±.036 | 2.32Β±.036 | 2.36Β±.037 |
| DNN-IPD | 0.48Β±.009 | 0.48Β±.009 | 0.48Β±.009 | | --- | --- | --- | --- | | Linear-IPD | 0.40Β±.008 | 0.40Β±.008 | 0.41Β±.008 |
1
| | 30dB | 20dB | 10dB | | --- | --- | --- | --- | | DNN-ILD | 3.03Β±.046 | 3.03Β±.046 | 3.05Β±.046 | | Linear-ILD | 2.31Β±.036 | 2.32Β±.036 | 2.36Β±.037 |
| DNN-IPD | 0.46Β±.008 | 0.48Β±.009 | 0.50Β±.009 | 0.54Β±.009 | | --- | --- | --- | --- | --- | | Linear-IPD | 0.17Β±.005 | 0.38Β±.008 | 0.53Β±.009 | 0.57Β±.010 |
0
| Link | Thedegreeofdependence | | --- | --- | | (S,S)115 | 0.7 |
| (S,S)511 | 0.6 | | --- | --- | | (S,S)1223 | 0.3 | | (S,S)2312 | 0.1 |
1
| Link | Thedegreeofdependence | | --- | --- | | (S,S)115 | 0.7 |
| Link | Thedegreeofdependence | | --- | --- | | (S,S)835 | 0.6 | | (S,S)358 | 0.2 | | (S,S)1013 | 0.7 | | (S,S)1310 | 0.3 |
0
| Link | Thedegreeofdependence | | --- | --- | | (S,S)115 | 0.7 | | (S,S)511 | 0.6 |
| (S,S)1223 | 0.3 | | --- | --- | | (S,S)2312 | 0.1 |
1
| Link | Thedegreeofdependence | | --- | --- | | (S,S)115 | 0.7 | | (S,S)511 | 0.6 |
| (S,S)358 | 0.2 | | --- | --- | | (S,S)1013 | 0.7 | | (S,S)1310 | 0.3 |
0
| Rule1 | Rule2 | Rule3 | | | | | | --- | --- | --- | --- | --- | --- | --- | | IG | CC | IG | CC | IG | CC | | | Age | 0 | 0.04 | 0 | 0 | 0 | -0.10 | | Gender | 0.06 | 0.14 | 0.06 | 0.13 | 0 | -0.06 |
| Job | 0.08 | -0.18 | 0.08 | -0.17 | 0.04 | 0.11 | | --- | --- | --- | --- | --- | --- | --- | | Studies | 0 | 0.18 | 0 | 0.16 | 0 | 0.017 | | Freq.ofuse | 0.03 | 0.05 | 0.06 | 0.08 | 0.02 | -0.07 | | #Accounts | 0 | 0.14 | 0 | 0.16 | 0 | -0.05 | | Priv.Concern | 0 | 0.13 | 0 | 0.16 | 0 | 0.04 |
1
| Rule1 | Rule2 | Rule3 | | | | | | --- | --- | --- | --- | --- | --- | --- | | IG | CC | IG | CC | IG | CC | | | Age | 0 | 0.04 | 0 | 0 | 0 | -0.10 | | Gender | 0.06 | 0.14 | 0.06 | 0.13 | 0 | -0.06 |
| Group | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 13 | rule | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | 77.80 | 63.41 | 51.43 | 81.72 | 81.49 | 76.23 | 81.41 | 78.60 | 81.49 | 81.49 | | 2 | 14.68 | 10.87 | 2.08 | 16.18 | 15.95 | 14.68 | 16.07 | 16.07 | 15.95 | 15.95 | | 3 | 65.94 | 41.16 | 33.62 | 72.75 | 72.75 | 69.06 | 68.98 | 70.48 | 74.17 | 72.75 | | 4 | 73.27 | 62.18 | 48.71 | 77.62 | 77.62 | 73.66 | 77.23 | 77.62 | 77.62 | 77.62 | | 5 | 27.75 | 18.77 | 17.66 | 28.86 | 28.86 | 21.39 | 29.87 | 28.86 | 28.86 | 28.86 | | 6 | 34.16 | 27.87 | 28.61 | 32.68 | 32.43 | 34.28 | 33.54 | 32.31 | 32.43 | 32.43 | | 7 | 88.66 | 63.19 | 71.83 | 89.56 | 89.56 | 86.33 | 89.93 | 89.26 | 89.56 | 89.56 | | 8 | 65.21 | 48.26 | 33.27 | 67.53 | 67.53 | 46.65 | 69.05 | 68.06 | 67.53 | 67.53 | | 9 | 70.90 | 60.00 | 61.90 | 73.18 | 73.18 | 61.99 | 71.09 | 72.70 | 74.41 | 73.18 | | 10 | 85.17 | 83.79 | 71.78 | 85.42 | 85.42 | 82.23 | 85.36 | 85.36 | 85.42 | 85.42 | | 11 | 62.92 | 43.30 | 48.69 | 68.44 | 66.20 | 64.27 | 64.46 | 66.13 | 66.20 | 66.20 | | 12 | 76.93 | 74.76 | 74.68 | 78.36 | 78.36 | 75.13 | 78.21 | 78.14 | 78.36 | 78.36 | | 13 | 55.12 | 21.75 | 29.69 | 65.71 | 63.87 | 56.85 | 62.83 | 62.83 | 63.87 | 63.87 |
0
| Rule1 | Rule2 | Rule3 | | | | | | --- | --- | --- | --- | --- | --- | --- | | IG | CC | IG | CC | IG | CC | | | Age | 0 | 0.04 | 0 | 0 | 0 | -0.10 | | Gender | 0.06 | 0.14 | 0.06 | 0.13 | 0 | -0.06 | | Job | 0.08 | -0.18 | 0.08 | -0.17 | 0.04 | 0.11 | | Studies | 0 | 0.18 | 0 | 0.16 | 0 | 0.017 |
| Freq.ofuse | 0.03 | 0.05 | 0.06 | 0.08 | 0.02 | -0.07 | | --- | --- | --- | --- | --- | --- | --- | | #Accounts | 0 | 0.14 | 0 | 0.16 | 0 | -0.05 | | Priv.Concern | 0 | 0.13 | 0 | 0.16 | 0 | 0.04 |
1
| Rule1 | Rule2 | Rule3 | | | | | | --- | --- | --- | --- | --- | --- | --- | | IG | CC | IG | CC | IG | CC | | | Age | 0 | 0.04 | 0 | 0 | 0 | -0.10 | | Gender | 0.06 | 0.14 | 0.06 | 0.13 | 0 | -0.06 | | Job | 0.08 | -0.18 | 0.08 | -0.17 | 0.04 | 0.11 | | Studies | 0 | 0.18 | 0 | 0.16 | 0 | 0.017 |
| 3 | 65.94 | 41.16 | 33.62 | 72.75 | 72.75 | 69.06 | 68.98 | 70.48 | 74.17 | 72.75 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 4 | 73.27 | 62.18 | 48.71 | 77.62 | 77.62 | 73.66 | 77.23 | 77.62 | 77.62 | 77.62 | | 5 | 27.75 | 18.77 | 17.66 | 28.86 | 28.86 | 21.39 | 29.87 | 28.86 | 28.86 | 28.86 | | 6 | 34.16 | 27.87 | 28.61 | 32.68 | 32.43 | 34.28 | 33.54 | 32.31 | 32.43 | 32.43 | | 7 | 88.66 | 63.19 | 71.83 | 89.56 | 89.56 | 86.33 | 89.93 | 89.26 | 89.56 | 89.56 | | 8 | 65.21 | 48.26 | 33.27 | 67.53 | 67.53 | 46.65 | 69.05 | 68.06 | 67.53 | 67.53 | | 9 | 70.90 | 60.00 | 61.90 | 73.18 | 73.18 | 61.99 | 71.09 | 72.70 | 74.41 | 73.18 | | 10 | 85.17 | 83.79 | 71.78 | 85.42 | 85.42 | 82.23 | 85.36 | 85.36 | 85.42 | 85.42 | | 11 | 62.92 | 43.30 | 48.69 | 68.44 | 66.20 | 64.27 | 64.46 | 66.13 | 66.20 | 66.20 | | 12 | 76.93 | 74.76 | 74.68 | 78.36 | 78.36 | 75.13 | 78.21 | 78.14 | 78.36 | 78.36 | | 13 | 55.12 | 21.75 | 29.69 | 65.71 | 63.87 | 56.85 | 62.83 | 62.83 | 63.87 | 63.87 |
0
| (30,5,24,2βˆ’2βˆ’2)<br>371816<br>(38,5,32,2βˆ’2βˆ’2)<br>4321186βˆ—<br>(44,5,38,2βˆ’2βˆ’2βˆ’2)<br>5326216βˆ—<br>(54,5,48,2βˆ’2βˆ’2βˆ’2)<br>5929236βˆ—<br>(60,5,54,2βˆ’2βˆ’2βˆ’2)<br>6934266βˆ—<br>(70,5,64,2βˆ’2βˆ’2βˆ’2)<br>7537286βˆ—<br>(76,5,70,2βˆ’2βˆ’2βˆ’2)<br>8341306βˆ—<br>(84,5,78,2βˆ’2βˆ’2βˆ’2)<br>8944326βˆ—<br>(90,5,84,2βˆ’2βˆ’2βˆ’2)<br>974834326βˆ—<br>(98,5,92,2βˆ’2βˆ’2βˆ’2βˆ’2) | (36,5,30,2βˆ’2βˆ’2βˆ’2)<br>412017146βˆ—<br>(42,5,36,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723196βˆ—<br>(48,5,42,2βˆ’2βˆ’2βˆ’2)<br>572822216βˆ—<br>(58,5,52,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6331246βˆ—<br>(64,5,48,2βˆ’2βˆ’2βˆ’2)<br>733627246βˆ—<br>(74,5,68,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939296βˆ—<br>(80,5,74,2βˆ’2βˆ’2βˆ’2)<br>874331306βˆ—<br>(88,5,82,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9346336βˆ—<br>(94,5,88,2βˆ’2βˆ’2βˆ’2)<br>9949356βˆ—<br>(100,5,94,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (34,6,27,2βˆ’2βˆ’2)<br>412018<br>(42,6,35,2βˆ’2βˆ’2)<br>512522<br>(52,6,45,2βˆ’2βˆ’2)<br>5929247βˆ—<br>(60,6,53,2βˆ’2βˆ’2βˆ’2)<br>6532267βˆ—<br>(66,6,59,2βˆ’2βˆ’2βˆ’2)<br>7537297βˆ—<br>(76,6,69,2βˆ’2βˆ’2βˆ’2)<br>8140317βˆ—<br>(82,6,75,2βˆ’2βˆ’2βˆ’2)<br>894433327βˆ—<br>(90,6,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9547357βˆ—<br>(96,6,89,2βˆ’2βˆ’2βˆ’2) | (40,6,33,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723207βˆ—<br>(48,6,41,2βˆ’2βˆ’2βˆ’2)<br>5326227βˆ—<br>(54,6,47,2βˆ’2βˆ’2βˆ’2)<br>633125247βˆ—<br>(64,6,47,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6934277βˆ—<br>(70,6,63,2βˆ’2βˆ’2βˆ’2)<br>793930297βˆ—<br>(80,6,73,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8542327βˆ—<br>(86,6,79,2βˆ’2βˆ’2βˆ’2)<br>9145347βˆ—<br>(92,6,85,2βˆ’2βˆ’2βˆ’2)<br>994936357βˆ—<br>(100,6,93,2βˆ’2βˆ’2βˆ’2βˆ’2) |
| (38,7,30,2βˆ’2βˆ’2βˆ’2)<br>452220<br>(46,7,38,2βˆ’2βˆ’2)<br>512522218βˆ—<br>(52,7,44,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>572824238βˆ—<br>(58,7,50,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>633126258βˆ—<br>(64,7,46,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>693428278βˆ—<br>(70,7,62,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7337308βˆ—<br>(76,7,68,2βˆ’2βˆ’2βˆ’2)<br>8140328βˆ—<br>(82,7,74,2βˆ’2βˆ’2βˆ’2)<br>8743348βˆ—<br>(88,7,80,2βˆ’2βˆ’2βˆ’2)<br>9748378βˆ—<br>(98,7,90,2βˆ’2βˆ’2βˆ’2) | (40,7,32,2βˆ’2βˆ’2)<br>472321<br>(48,7,40,2βˆ’2βˆ’2)<br>532623<br>(54,7,46,2βˆ’2βˆ’2)<br>5929258βˆ—<br>(60,7,52,2βˆ’2βˆ’2βˆ’2)<br>6532278βˆ—<br>(66,7,58,2βˆ’2βˆ’2βˆ’2)<br>7135298βˆ—<br>(72,7,64,2βˆ’2βˆ’2βˆ’2)<br>7738318βˆ—<br>(78,7,70,2βˆ’2βˆ’2βˆ’2)<br>854233328βˆ—<br>(86,7,78,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9145358βˆ—<br>(92,7,84,2βˆ’2βˆ’2βˆ’2)<br>9949388βˆ—<br>(100,7,92,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (42,8,33,2βˆ’2βˆ’2βˆ’2)<br>49242221<br>(50,8,41,2βˆ’2βˆ’2βˆ’2)<br>5728259βˆ—<br>(58,8,49,2βˆ’2βˆ’2βˆ’2)<br>67332529<br>(68,8,59,2βˆ’2βˆ’2βˆ’2)<br>7135309βˆ—<br>(72,8,63,2βˆ’2βˆ’2βˆ’2)<br>7738329βˆ—<br>(78,8,69,2βˆ’2βˆ’2βˆ’2)<br>8743359βˆ—<br>(88,8,79,2βˆ’2βˆ’2βˆ’2)<br>9346379βˆ—<br>(94,8,85,2βˆ’2βˆ’2βˆ’2)<br>9949399βˆ—<br>(100,8,91,2βˆ’2βˆ’2βˆ’2) | (44,8,35,2βˆ’2βˆ’2)<br>512523<br>(52,8,43,2βˆ’2βˆ’2)<br>6331279βˆ—<br>(64,8,45,2βˆ’2βˆ’2βˆ’2)<br>693429279βˆ—<br>(70,8,61,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>753731289βˆ—<br>(76,8,67,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8140339βˆ—<br>(82,8,73,2βˆ’2βˆ’2βˆ’2)<br>914536359βˆ—<br>(92,8,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>974838369βˆ—<br>(98,8,89,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>19999689βˆ—<br>(200,8,191,2βˆ’2βˆ’2βˆ’2) | | (46,9,36,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>5326242322<br>(54,9,44,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>61302726<br>(62,9,52,2βˆ’2βˆ’2βˆ’2)<br>673329282710βˆ—<br>(68,9,58,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>733632<br>(74,9,64,2βˆ’2βˆ’2<br>79393410βˆ—<br>(80,9,70,2βˆ’2βˆ’2βˆ’2)<br>87433610βˆ—<br>(88,9,78,2βˆ’2βˆ’2βˆ’2)<br>9748393810βˆ—<br>(98,9,88,2βˆ’2βˆ’2βˆ’2βˆ’2) | (48,9,38,2βˆ’2βˆ’2)<br>552725<br>(56,9,46,2βˆ’2βˆ’2)<br>633128<br>(64,9,44,2βˆ’2βˆ’2)<br>69343010βˆ—<br>(70,9,60,2βˆ’2βˆ’2βˆ’2)<br>75373210βˆ—<br>(76,9,66,2βˆ’2βˆ’2βˆ’2)<br>81403410βˆ—<br>(82,9,72,2βˆ’2βˆ’2βˆ’2)<br>93463810βˆ—<br>(94,9,84,2βˆ’2βˆ’2βˆ’2)<br>99494010βˆ—<br>(100,9,90,2βˆ’2βˆ’2βˆ’2) | | (52,10,41,2βˆ’2βˆ’2)<br>βˆ—6532292827262511<br>(66,10,55,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7336323011βˆ—<br>(74,10,63,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939343311βˆ—<br>(80,10,69,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>83413611βˆ—<br>(84,10,73,2βˆ’2βˆ’2βˆ’2)<br>87433711βˆ—<br>(88,10,77,2βˆ’2βˆ’2βˆ’2)<br>93463911βˆ—<br>(94,10,83,2βˆ’2βˆ’2βˆ’2)<br>99494111βˆ—<br>(100,10,89,2βˆ’2βˆ’2βˆ’2) | (60,10,49,2βˆ’2βˆ’2)<br>673330<br>(68,10,57,2βˆ’2βˆ’2)<br>753733<br>(76,10,65,2βˆ’2βˆ’2)<br>81403511βˆ—<br>(82,10,71,2βˆ’2βˆ’2βˆ’2)<br>854236353411βˆ—<br>(86,10,75,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>91453837363511βˆ—<br>(92,10,81,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>974840393811βˆ—<br>(98,10,87,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>49924915311βˆ—<br>(500,10,489,2βˆ’2βˆ’2βˆ’2) | | (100,21,78,2βˆ’2βˆ’2)<br>18391898786<br>(184,38,145,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>831415414413<br>(832,200,631,2βˆ’2βˆ’2βˆ’2) | (200,45,154,2βˆ’2βˆ’2)<br>515255253<br>(516,116,399,2βˆ’2βˆ’2)<br>99994999499849974996<br>(10000,2475,7524,2βˆ’2βˆ’2βˆ’2βˆ’2) |
1
| (30,5,24,2βˆ’2βˆ’2)<br>371816<br>(38,5,32,2βˆ’2βˆ’2)<br>4321186βˆ—<br>(44,5,38,2βˆ’2βˆ’2βˆ’2)<br>5326216βˆ—<br>(54,5,48,2βˆ’2βˆ’2βˆ’2)<br>5929236βˆ—<br>(60,5,54,2βˆ’2βˆ’2βˆ’2)<br>6934266βˆ—<br>(70,5,64,2βˆ’2βˆ’2βˆ’2)<br>7537286βˆ—<br>(76,5,70,2βˆ’2βˆ’2βˆ’2)<br>8341306βˆ—<br>(84,5,78,2βˆ’2βˆ’2βˆ’2)<br>8944326βˆ—<br>(90,5,84,2βˆ’2βˆ’2βˆ’2)<br>974834326βˆ—<br>(98,5,92,2βˆ’2βˆ’2βˆ’2βˆ’2) | (36,5,30,2βˆ’2βˆ’2βˆ’2)<br>412017146βˆ—<br>(42,5,36,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723196βˆ—<br>(48,5,42,2βˆ’2βˆ’2βˆ’2)<br>572822216βˆ—<br>(58,5,52,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6331246βˆ—<br>(64,5,48,2βˆ’2βˆ’2βˆ’2)<br>733627246βˆ—<br>(74,5,68,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939296βˆ—<br>(80,5,74,2βˆ’2βˆ’2βˆ’2)<br>874331306βˆ—<br>(88,5,82,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9346336βˆ—<br>(94,5,88,2βˆ’2βˆ’2βˆ’2)<br>9949356βˆ—<br>(100,5,94,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (34,6,27,2βˆ’2βˆ’2)<br>412018<br>(42,6,35,2βˆ’2βˆ’2)<br>512522<br>(52,6,45,2βˆ’2βˆ’2)<br>5929247βˆ—<br>(60,6,53,2βˆ’2βˆ’2βˆ’2)<br>6532267βˆ—<br>(66,6,59,2βˆ’2βˆ’2βˆ’2)<br>7537297βˆ—<br>(76,6,69,2βˆ’2βˆ’2βˆ’2)<br>8140317βˆ—<br>(82,6,75,2βˆ’2βˆ’2βˆ’2)<br>894433327βˆ—<br>(90,6,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9547357βˆ—<br>(96,6,89,2βˆ’2βˆ’2βˆ’2) | (40,6,33,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723207βˆ—<br>(48,6,41,2βˆ’2βˆ’2βˆ’2)<br>5326227βˆ—<br>(54,6,47,2βˆ’2βˆ’2βˆ’2)<br>633125247βˆ—<br>(64,6,47,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6934277βˆ—<br>(70,6,63,2βˆ’2βˆ’2βˆ’2)<br>793930297βˆ—<br>(80,6,73,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8542327βˆ—<br>(86,6,79,2βˆ’2βˆ’2βˆ’2)<br>9145347βˆ—<br>(92,6,85,2βˆ’2βˆ’2βˆ’2)<br>994936357βˆ—<br>(100,6,93,2βˆ’2βˆ’2βˆ’2βˆ’2) |
| | | | | --- | --- | --- | | | | | | d1<br>d2<br>d3 | 0,27Γ—104480,25Γ—10<br>291761203628673<br>666<br>0,50Γ—100,45Γ—100,30Γ—10 | 2,58Γ—10752,58Γ—10<br>66<br>4,12Γ—103474,11Γ—10<br>666<br>24,45Γ—1019,62Γ—103,46Γ—10 | | total | 0,80Γ—100,46Γ—100,58Γ—10 | 31,15Γ—1019,62Γ—1010,16Γ—10 | | DBLP | Netflix | | | | | | | d1<br>d2<br>d3 | 0,79Γ—102370,55Γ—10<br>66<br>2,62Γ—10424070,97Γ—10<br>666<br>3,27Γ—101,61Γ—101,61Γ—10 | 15,54Γ—1025612,47Γ—10<br>966<br>0,19Γ—100,14Γ—1020,30Γ—10<br>966<br>0,20Γ—1044,52Γ—100,92Γ—10 | | total | 6,68Γ—101,61Γ—102,13Γ—10 | 0,39Γ—1044,66Γ—1033,69Γ—10 |
0
| (30,5,24,2βˆ’2βˆ’2)<br>371816<br>(38,5,32,2βˆ’2βˆ’2)<br>4321186βˆ—<br>(44,5,38,2βˆ’2βˆ’2βˆ’2)<br>5326216βˆ—<br>(54,5,48,2βˆ’2βˆ’2βˆ’2)<br>5929236βˆ—<br>(60,5,54,2βˆ’2βˆ’2βˆ’2)<br>6934266βˆ—<br>(70,5,64,2βˆ’2βˆ’2βˆ’2)<br>7537286βˆ—<br>(76,5,70,2βˆ’2βˆ’2βˆ’2)<br>8341306βˆ—<br>(84,5,78,2βˆ’2βˆ’2βˆ’2)<br>8944326βˆ—<br>(90,5,84,2βˆ’2βˆ’2βˆ’2)<br>974834326βˆ—<br>(98,5,92,2βˆ’2βˆ’2βˆ’2βˆ’2) | (36,5,30,2βˆ’2βˆ’2βˆ’2)<br>412017146βˆ—<br>(42,5,36,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723196βˆ—<br>(48,5,42,2βˆ’2βˆ’2βˆ’2)<br>572822216βˆ—<br>(58,5,52,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6331246βˆ—<br>(64,5,48,2βˆ’2βˆ’2βˆ’2)<br>733627246βˆ—<br>(74,5,68,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939296βˆ—<br>(80,5,74,2βˆ’2βˆ’2βˆ’2)<br>874331306βˆ—<br>(88,5,82,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9346336βˆ—<br>(94,5,88,2βˆ’2βˆ’2βˆ’2)<br>9949356βˆ—<br>(100,5,94,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (34,6,27,2βˆ’2βˆ’2)<br>412018<br>(42,6,35,2βˆ’2βˆ’2)<br>512522<br>(52,6,45,2βˆ’2βˆ’2)<br>5929247βˆ—<br>(60,6,53,2βˆ’2βˆ’2βˆ’2)<br>6532267βˆ—<br>(66,6,59,2βˆ’2βˆ’2βˆ’2)<br>7537297βˆ—<br>(76,6,69,2βˆ’2βˆ’2βˆ’2)<br>8140317βˆ—<br>(82,6,75,2βˆ’2βˆ’2βˆ’2)<br>894433327βˆ—<br>(90,6,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9547357βˆ—<br>(96,6,89,2βˆ’2βˆ’2βˆ’2) | (40,6,33,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723207βˆ—<br>(48,6,41,2βˆ’2βˆ’2βˆ’2)<br>5326227βˆ—<br>(54,6,47,2βˆ’2βˆ’2βˆ’2)<br>633125247βˆ—<br>(64,6,47,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6934277βˆ—<br>(70,6,63,2βˆ’2βˆ’2βˆ’2)<br>793930297βˆ—<br>(80,6,73,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8542327βˆ—<br>(86,6,79,2βˆ’2βˆ’2βˆ’2)<br>9145347βˆ—<br>(92,6,85,2βˆ’2βˆ’2βˆ’2)<br>994936357βˆ—<br>(100,6,93,2βˆ’2βˆ’2βˆ’2βˆ’2) | | (38,7,30,2βˆ’2βˆ’2βˆ’2)<br>452220<br>(46,7,38,2βˆ’2βˆ’2)<br>512522218βˆ—<br>(52,7,44,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>572824238βˆ—<br>(58,7,50,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>633126258βˆ—<br>(64,7,46,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>693428278βˆ—<br>(70,7,62,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7337308βˆ—<br>(76,7,68,2βˆ’2βˆ’2βˆ’2)<br>8140328βˆ—<br>(82,7,74,2βˆ’2βˆ’2βˆ’2)<br>8743348βˆ—<br>(88,7,80,2βˆ’2βˆ’2βˆ’2)<br>9748378βˆ—<br>(98,7,90,2βˆ’2βˆ’2βˆ’2) | (40,7,32,2βˆ’2βˆ’2)<br>472321<br>(48,7,40,2βˆ’2βˆ’2)<br>532623<br>(54,7,46,2βˆ’2βˆ’2)<br>5929258βˆ—<br>(60,7,52,2βˆ’2βˆ’2βˆ’2)<br>6532278βˆ—<br>(66,7,58,2βˆ’2βˆ’2βˆ’2)<br>7135298βˆ—<br>(72,7,64,2βˆ’2βˆ’2βˆ’2)<br>7738318βˆ—<br>(78,7,70,2βˆ’2βˆ’2βˆ’2)<br>854233328βˆ—<br>(86,7,78,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9145358βˆ—<br>(92,7,84,2βˆ’2βˆ’2βˆ’2)<br>9949388βˆ—<br>(100,7,92,2βˆ’2βˆ’2βˆ’2) |
| (42,8,33,2βˆ’2βˆ’2βˆ’2)<br>49242221<br>(50,8,41,2βˆ’2βˆ’2βˆ’2)<br>5728259βˆ—<br>(58,8,49,2βˆ’2βˆ’2βˆ’2)<br>67332529<br>(68,8,59,2βˆ’2βˆ’2βˆ’2)<br>7135309βˆ—<br>(72,8,63,2βˆ’2βˆ’2βˆ’2)<br>7738329βˆ—<br>(78,8,69,2βˆ’2βˆ’2βˆ’2)<br>8743359βˆ—<br>(88,8,79,2βˆ’2βˆ’2βˆ’2)<br>9346379βˆ—<br>(94,8,85,2βˆ’2βˆ’2βˆ’2)<br>9949399βˆ—<br>(100,8,91,2βˆ’2βˆ’2βˆ’2) | (44,8,35,2βˆ’2βˆ’2)<br>512523<br>(52,8,43,2βˆ’2βˆ’2)<br>6331279βˆ—<br>(64,8,45,2βˆ’2βˆ’2βˆ’2)<br>693429279βˆ—<br>(70,8,61,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>753731289βˆ—<br>(76,8,67,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8140339βˆ—<br>(82,8,73,2βˆ’2βˆ’2βˆ’2)<br>914536359βˆ—<br>(92,8,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>974838369βˆ—<br>(98,8,89,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>19999689βˆ—<br>(200,8,191,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (46,9,36,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>5326242322<br>(54,9,44,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>61302726<br>(62,9,52,2βˆ’2βˆ’2βˆ’2)<br>673329282710βˆ—<br>(68,9,58,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>733632<br>(74,9,64,2βˆ’2βˆ’2<br>79393410βˆ—<br>(80,9,70,2βˆ’2βˆ’2βˆ’2)<br>87433610βˆ—<br>(88,9,78,2βˆ’2βˆ’2βˆ’2)<br>9748393810βˆ—<br>(98,9,88,2βˆ’2βˆ’2βˆ’2βˆ’2) | (48,9,38,2βˆ’2βˆ’2)<br>552725<br>(56,9,46,2βˆ’2βˆ’2)<br>633128<br>(64,9,44,2βˆ’2βˆ’2)<br>69343010βˆ—<br>(70,9,60,2βˆ’2βˆ’2βˆ’2)<br>75373210βˆ—<br>(76,9,66,2βˆ’2βˆ’2βˆ’2)<br>81403410βˆ—<br>(82,9,72,2βˆ’2βˆ’2βˆ’2)<br>93463810βˆ—<br>(94,9,84,2βˆ’2βˆ’2βˆ’2)<br>99494010βˆ—<br>(100,9,90,2βˆ’2βˆ’2βˆ’2) | | (52,10,41,2βˆ’2βˆ’2)<br>βˆ—6532292827262511<br>(66,10,55,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7336323011βˆ—<br>(74,10,63,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939343311βˆ—<br>(80,10,69,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>83413611βˆ—<br>(84,10,73,2βˆ’2βˆ’2βˆ’2)<br>87433711βˆ—<br>(88,10,77,2βˆ’2βˆ’2βˆ’2)<br>93463911βˆ—<br>(94,10,83,2βˆ’2βˆ’2βˆ’2)<br>99494111βˆ—<br>(100,10,89,2βˆ’2βˆ’2βˆ’2) | (60,10,49,2βˆ’2βˆ’2)<br>673330<br>(68,10,57,2βˆ’2βˆ’2)<br>753733<br>(76,10,65,2βˆ’2βˆ’2)<br>81403511βˆ—<br>(82,10,71,2βˆ’2βˆ’2βˆ’2)<br>854236353411βˆ—<br>(86,10,75,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>91453837363511βˆ—<br>(92,10,81,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>974840393811βˆ—<br>(98,10,87,2βˆ’2βˆ’2βˆ’2βˆ’2βˆ’2)<br>49924915311βˆ—<br>(500,10,489,2βˆ’2βˆ’2βˆ’2) | | (100,21,78,2βˆ’2βˆ’2)<br>18391898786<br>(184,38,145,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>831415414413<br>(832,200,631,2βˆ’2βˆ’2βˆ’2) | (200,45,154,2βˆ’2βˆ’2)<br>515255253<br>(516,116,399,2βˆ’2βˆ’2)<br>99994999499849974996<br>(10000,2475,7524,2βˆ’2βˆ’2βˆ’2βˆ’2) |
1
| (30,5,24,2βˆ’2βˆ’2)<br>371816<br>(38,5,32,2βˆ’2βˆ’2)<br>4321186βˆ—<br>(44,5,38,2βˆ’2βˆ’2βˆ’2)<br>5326216βˆ—<br>(54,5,48,2βˆ’2βˆ’2βˆ’2)<br>5929236βˆ—<br>(60,5,54,2βˆ’2βˆ’2βˆ’2)<br>6934266βˆ—<br>(70,5,64,2βˆ’2βˆ’2βˆ’2)<br>7537286βˆ—<br>(76,5,70,2βˆ’2βˆ’2βˆ’2)<br>8341306βˆ—<br>(84,5,78,2βˆ’2βˆ’2βˆ’2)<br>8944326βˆ—<br>(90,5,84,2βˆ’2βˆ’2βˆ’2)<br>974834326βˆ—<br>(98,5,92,2βˆ’2βˆ’2βˆ’2βˆ’2) | (36,5,30,2βˆ’2βˆ’2βˆ’2)<br>412017146βˆ—<br>(42,5,36,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723196βˆ—<br>(48,5,42,2βˆ’2βˆ’2βˆ’2)<br>572822216βˆ—<br>(58,5,52,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6331246βˆ—<br>(64,5,48,2βˆ’2βˆ’2βˆ’2)<br>733627246βˆ—<br>(74,5,68,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7939296βˆ—<br>(80,5,74,2βˆ’2βˆ’2βˆ’2)<br>874331306βˆ—<br>(88,5,82,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9346336βˆ—<br>(94,5,88,2βˆ’2βˆ’2βˆ’2)<br>9949356βˆ—<br>(100,5,94,2βˆ’2βˆ’2βˆ’2) | | --- | --- | | (34,6,27,2βˆ’2βˆ’2)<br>412018<br>(42,6,35,2βˆ’2βˆ’2)<br>512522<br>(52,6,45,2βˆ’2βˆ’2)<br>5929247βˆ—<br>(60,6,53,2βˆ’2βˆ’2βˆ’2)<br>6532267βˆ—<br>(66,6,59,2βˆ’2βˆ’2βˆ’2)<br>7537297βˆ—<br>(76,6,69,2βˆ’2βˆ’2βˆ’2)<br>8140317βˆ—<br>(82,6,75,2βˆ’2βˆ’2βˆ’2)<br>894433327βˆ—<br>(90,6,83,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9547357βˆ—<br>(96,6,89,2βˆ’2βˆ’2βˆ’2) | (40,6,33,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>4723207βˆ—<br>(48,6,41,2βˆ’2βˆ’2βˆ’2)<br>5326227βˆ—<br>(54,6,47,2βˆ’2βˆ’2βˆ’2)<br>633125247βˆ—<br>(64,6,47,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>6934277βˆ—<br>(70,6,63,2βˆ’2βˆ’2βˆ’2)<br>793930297βˆ—<br>(80,6,73,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>8542327βˆ—<br>(86,6,79,2βˆ’2βˆ’2βˆ’2)<br>9145347βˆ—<br>(92,6,85,2βˆ’2βˆ’2βˆ’2)<br>994936357βˆ—<br>(100,6,93,2βˆ’2βˆ’2βˆ’2βˆ’2) | | (38,7,30,2βˆ’2βˆ’2βˆ’2)<br>452220<br>(46,7,38,2βˆ’2βˆ’2)<br>512522218βˆ—<br>(52,7,44,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>572824238βˆ—<br>(58,7,50,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>633126258βˆ—<br>(64,7,46,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>693428278βˆ—<br>(70,7,62,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>7337308βˆ—<br>(76,7,68,2βˆ’2βˆ’2βˆ’2)<br>8140328βˆ—<br>(82,7,74,2βˆ’2βˆ’2βˆ’2)<br>8743348βˆ—<br>(88,7,80,2βˆ’2βˆ’2βˆ’2)<br>9748378βˆ—<br>(98,7,90,2βˆ’2βˆ’2βˆ’2) | (40,7,32,2βˆ’2βˆ’2)<br>472321<br>(48,7,40,2βˆ’2βˆ’2)<br>532623<br>(54,7,46,2βˆ’2βˆ’2)<br>5929258βˆ—<br>(60,7,52,2βˆ’2βˆ’2βˆ’2)<br>6532278βˆ—<br>(66,7,58,2βˆ’2βˆ’2βˆ’2)<br>7135298βˆ—<br>(72,7,64,2βˆ’2βˆ’2βˆ’2)<br>7738318βˆ—<br>(78,7,70,2βˆ’2βˆ’2βˆ’2)<br>854233328βˆ—<br>(86,7,78,2βˆ’2βˆ’2βˆ’2βˆ’2)<br>9145358βˆ—<br>(92,7,84,2βˆ’2βˆ’2βˆ’2)<br>9949388βˆ—<br>(100,7,92,2βˆ’2βˆ’2βˆ’2) |
| d1<br>d2<br>d3 | 0,79Γ—102370,55Γ—10<br>66<br>2,62Γ—10424070,97Γ—10<br>666<br>3,27Γ—101,61Γ—101,61Γ—10 | 15,54Γ—1025612,47Γ—10<br>966<br>0,19Γ—100,14Γ—1020,30Γ—10<br>966<br>0,20Γ—1044,52Γ—100,92Γ—10 | | --- | --- | --- | | total | 6,68Γ—101,61Γ—102,13Γ—10 | 0,39Γ—1044,66Γ—1033,69Γ—10 |
0
| | AverageReward | TotalReward | K-DDifference | | --- | --- | --- | --- | | Game1 | 0.77 | 155.68 | 11 | | Game2 | 0.74 | 149.38 | 8 | | Game3 | 0.84 | 168.57 | 15 |
| Game4 | 0.61 | 122.12 | -8 | | --- | --- | --- | --- | | Game5 | 0.97 | 194.40 | 37 |
1
| | AverageReward | TotalReward | K-DDifference | | --- | --- | --- | --- | | Game1 | 0.77 | 155.68 | 11 | | Game2 | 0.74 | 149.38 | 8 | | Game3 | 0.84 | 168.57 | 15 |
| MeanRank | | | | --- | --- | --- | | 210 | 119 | 48.5 | | 212 | 87 | 45.7 | | 167 | 39 | 51.7 | | 200 | 113 | 44.3 | | 181 | 93 | 49.6 | | 213 | 113 | 52.0 | | 188 | 85 | 53.5 | | MeanRank | | | | 263 | 251 | 75.4 | | 401 | 338 | 73.0 | | 312 | 193 | 81.3 | | 168 | 156 | 81.2 |
0
| | AverageReward | TotalReward | K-DDifference | | --- | --- | --- | --- | | Game1 | 0.77 | 155.68 | 11 |
| Game2 | 0.74 | 149.38 | 8 | | --- | --- | --- | --- | | Game3 | 0.84 | 168.57 | 15 | | Game4 | 0.61 | 122.12 | -8 | | Game5 | 0.97 | 194.40 | 37 |
1
| | AverageReward | TotalReward | K-DDifference | | --- | --- | --- | --- | | Game1 | 0.77 | 155.68 | 11 |
| 167 | 39 | 51.7 | | --- | --- | --- | | 200 | 113 | 44.3 | | 181 | 93 | 49.6 | | 213 | 113 | 52.0 | | 188 | 85 | 53.5 | | MeanRank | | | | 263 | 251 | 75.4 | | 401 | 338 | 73.0 | | 312 | 193 | 81.3 | | 168 | 156 | 81.2 |
0