premise string | hypothesis string | label int64 |
|---|---|---|
| state | powerconsumption(inWatts) |
| --- | --- |
| BUSY | 240 |
| IDLE | 150 | | | SLEEP | 10 |
| --- | --- |
| OFF | 0 | | 1 |
| state | powerconsumption(inWatts) |
| --- | --- |
| BUSY | 240 |
| IDLE | 150 | | | Parameter | 32-bit | | |
| --- | --- | --- | --- |
| Silicon | Carbon | Silicon | |
| Totalpowerdissipation<br>(watts) | 323.358µ | 76.8077n | 957.513µ |
| Averagepower<br>consumption(watts) | 43.834E-05 | 11.923E-05 | 122.50E-05 |
| PropagationDelay(s) | 262.36p | 680.36f | 280.43p |
| Powerdelayproduct(J) | 115E-15 | 81.1E-15 | 343.52E-15 | | 0 |
| state | powerconsumption(inWatts) |
| --- | --- |
| BUSY | 240 |
| IDLE | 150 | | | SLEEP | 10 |
| --- | --- |
| OFF | 0 | | 1 |
| state | powerconsumption(inWatts) |
| --- | --- |
| BUSY | 240 |
| IDLE | 150 | | | Totalpowerdissipation<br>(watts) | 323.358µ | 76.8077n | 957.513µ |
| --- | --- | --- | --- |
| Averagepower<br>consumption(watts) | 43.834E-05 | 11.923E-05 | 122.50E-05 |
| PropagationDelay(s) | 262.36p | 680.36f | 280.43p |
| Powerdelayproduct(J) | 115E-15 | 81.1E-15 | 343.52E-15 | | 0 |
| IntegratedSafetyandSecurityRisk<br>AssessmentMethod | Year | Country | Citations |
| --- | --- | --- | --- |
| EFT | 2009 | Italy | 63 |
| ExtendedCFT | 2013 | Germany | 17 |
| FACTGraph | 2015 | Singapore | 5 | | | CHASSIS | 2015 | Austria | 4 |
| --- | --- | --- | --- |
| FMVEA | 2014 | Austria | 4 |
| SAHARA | 2015 | Austria | 2 |
| UnifiedSecurityandSafetyRiskAssessment | 2014 | Taiwan | 1 | | 1 |
| IntegratedSafetyandSecurityRisk<br>AssessmentMethod | Year | Country | Citations |
| --- | --- | --- | --- |
| EFT | 2009 | Italy | 63 |
| ExtendedCFT | 2013 | Germany | 17 |
| FACTGraph | 2015 | Singapore | 5 | | | Code | Region | Numberofpatents |
| --- | --- | --- |
| WO | WorldIntellectualPropertyOrganization | 292 |
| EP | EuropeanPatentOffice | 163 |
| KR | RepublicofKorea | 51 |
| RU | RussianFederation | 5 |
| ZA | SouthAfrica | 3 |
| IL | Israel | 3 |
| ES | Spain | 3 |
| SG | Singapore | 2 |
| MX | Mexico | 1 | | 0 |
| IntegratedSafetyandSecurityRisk<br>AssessmentMethod | Year | Country | Citations |
| --- | --- | --- | --- |
| EFT | 2009 | Italy | 63 |
| ExtendedCFT | 2013 | Germany | 17 |
| FACTGraph | 2015 | Singapore | 5 | | | CHASSIS | 2015 | Austria | 4 |
| --- | --- | --- | --- |
| FMVEA | 2014 | Austria | 4 |
| SAHARA | 2015 | Austria | 2 |
| UnifiedSecurityandSafetyRiskAssessment | 2014 | Taiwan | 1 | | 1 |
| IntegratedSafetyandSecurityRisk<br>AssessmentMethod | Year | Country | Citations |
| --- | --- | --- | --- |
| EFT | 2009 | Italy | 63 |
| ExtendedCFT | 2013 | Germany | 17 |
| FACTGraph | 2015 | Singapore | 5 | | | KR | RepublicofKorea | 51 |
| --- | --- | --- |
| RU | RussianFederation | 5 |
| ZA | SouthAfrica | 3 |
| IL | Israel | 3 |
| ES | Spain | 3 |
| SG | Singapore | 2 |
| MX | Mexico | 1 | | 0 |
| PNMM | |
| --- | --- |
| 5Endmembers | 8Endmembers | | | Alg.(N)b | RMSE | RET(BS+HU) | RMSE | RET(BS+HU) |
| --- | --- | --- | --- | --- |
| FCLS | 0.1966 | 1 | 0.1521 | 1 |
| SK-Hype | 0.1127 | 3744.9 | 0.0765 | 3672.2 |
| SK-Hype(10) | 0.1131 | 21.7(24.3) | 0.0827 | 21.5(24.4) |
| SK-Hype(100) | 0.1140 | 153.4(184.2) | 0.0771 | 140.3(170.8) |
| SK-Hype(300) | 0.1129 | 1764.3(1907.5) | 0.0765 | 1601.0(1743.7) |
| | GBM | | | |
| | 5Endmembers | 8Endmembers | | |
| FCLS | 0.0527 | 1 | 0.0390 | 1 |
| SK-Hype | 0.1090 | 3432.5 | 0.0745 | 3825.1 |
| SK-Hype(10) | 0.1053 | 20.8(23.6) | 0.0730 | 20.9(23.0) |
| SK-Hype(100) | 0.1105 | 142.2(171.5) | 0.0748 | 142.9(173.8) |
| SK-Hype(300) | 0.1093 | 1612.8(1735.2) | 0.0745 | 1637.8(1778.1) | | 1 |
| PNMM | |
| --- | --- |
| 5Endmembers | 8Endmembers | | | PNMM | | | | |
| --- | --- | --- | --- | --- |
| | 5endmembers | 8endmembers | | |
| Alg.(N)b | RMSE | RET(BS+HU) | RMSE | RET(BS+HU) |
| FCLS | 0.1893 | 1 | 0.1243 | 1 |
| SK-Hype | 0.1136 | 2690.6 | 0.0762 | 3028.8 |
| SK-Hype(10) | 0.1114 | 16.0(18.1) | 0.0775 | 16.8(18.7) |
| SK-Hype(100) | 0.1150 | 107.7(129.1) | 0.0766 | 118.6(144.8) |
| SK-Hype(300) | 0.1139 | 1226.7(1327.1) | 0.0763 | 1331.5(1452.7) |
| | GBM | | | |
| FCLS | 0.2419 | 1 | 0.1836 | 1 |
| SK-Hype | 0.1080 | 3320.7 | 0.0738 | 3072.6 |
| SK-Hype(10) | 0.1037 | 24.1(26.9) | 0.0712 | 18.7(21.1) |
| SK-Hype(100) | 0.1095 | 157.0(194.6) | 0.0741 | 119.7(148.1) |
| SK-Hype(300) | 0.1083 | 1548.6(1676.0) | 0.0738 | 1475.2(1597.7) | | 0 |
| PNMM | |
| --- | --- |
| 5Endmembers | 8Endmembers | | | Alg.(N)b | RMSE | RET(BS+HU) | RMSE | RET(BS+HU) |
| --- | --- | --- | --- | --- |
| FCLS | 0.1966 | 1 | 0.1521 | 1 |
| SK-Hype | 0.1127 | 3744.9 | 0.0765 | 3672.2 |
| SK-Hype(10) | 0.1131 | 21.7(24.3) | 0.0827 | 21.5(24.4) |
| SK-Hype(100) | 0.1140 | 153.4(184.2) | 0.0771 | 140.3(170.8) |
| SK-Hype(300) | 0.1129 | 1764.3(1907.5) | 0.0765 | 1601.0(1743.7) |
| | GBM | | | |
| | 5Endmembers | 8Endmembers | | |
| FCLS | 0.0527 | 1 | 0.0390 | 1 |
| SK-Hype | 0.1090 | 3432.5 | 0.0745 | 3825.1 |
| SK-Hype(10) | 0.1053 | 20.8(23.6) | 0.0730 | 20.9(23.0) |
| SK-Hype(100) | 0.1105 | 142.2(171.5) | 0.0748 | 142.9(173.8) |
| SK-Hype(300) | 0.1093 | 1612.8(1735.2) | 0.0745 | 1637.8(1778.1) | | 1 |
| PNMM | |
| --- | --- |
| 5Endmembers | 8Endmembers | | | SK-Hype(10) | 0.1037 | 24.1(26.9) | 0.0712 | 18.7(21.1) |
| --- | --- | --- | --- | --- |
| SK-Hype(100) | 0.1095 | 157.0(194.6) | 0.0741 | 119.7(148.1) |
| SK-Hype(300) | 0.1083 | 1548.6(1676.0) | 0.0738 | 1475.2(1597.7) | | 0 |
| | facedetection | eyedetection | Time(s) |
| --- | --- | --- | --- |
| Originalimage | 0.297 | 0.58 | NULL | | | Lowrank+sparsity | 0.375 | 0.70 | 10 |
| --- | --- | --- | --- |
| Multiscalelowrank | 0.359 | 1.00 | 4472 |
| IBTSVT | 0.844 | 1.00 | 715 | | 1 |
| | facedetection | eyedetection | Time(s) |
| --- | --- | --- | --- |
| Originalimage | 0.297 | 0.58 | NULL | | | Operation | Mean | Max | 99pct. | Stdev. |
| --- | --- | --- | --- | --- |
| Imagecapture | 1.61 | 1.81 | 1.75 | 0.05 |
| Imagepre-processing | 2.77 | 2.90 | 2.87 | 0.04 |
| CNNinferencing | 18.49 | 19.30 | 18.99 | 0.20 |
| TotalTime | 22.86 | 23.74 | 23.38 | 0.20 | | 0 |
| | facedetection | eyedetection | Time(s) |
| --- | --- | --- | --- |
| Originalimage | 0.297 | 0.58 | NULL | | | Lowrank+sparsity | 0.375 | 0.70 | 10 |
| --- | --- | --- | --- |
| Multiscalelowrank | 0.359 | 1.00 | 4472 |
| IBTSVT | 0.844 | 1.00 | 715 | | 1 |
| | facedetection | eyedetection | Time(s) |
| --- | --- | --- | --- |
| Originalimage | 0.297 | 0.58 | NULL | | | Imagepre-processing | 2.77 | 2.90 | 2.87 | 0.04 |
| --- | --- | --- | --- | --- |
| CNNinferencing | 18.49 | 19.30 | 18.99 | 0.20 |
| TotalTime | 22.86 | 23.74 | 23.38 | 0.20 | | 0 |
| | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 18.9 | 17.8 | 18.9 | 19.4 | 18.6 | 20.0 | | | O2 | 18.7 | 17.9 | 18.7 | 19.3 | 18.4 | 19.8 |
| --- | --- | --- | --- | --- | --- | --- |
| O3 | 17.9 | 17.2 | 17.7 | 18.3 | 17.9 | 18.8 |
| O4 | 18.6 | 17.7 | 18.5 | 19.1 | 19.0 | 19.7 |
| O5 | 18.7 | 17.6 | 18.4 | 18.9 | 19.1 | 19.5 |
| O6 | 18.8 | 17.3 | 19.0 | 19.7 | 19.3 | 20.2 | | 1 |
| | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 18.9 | 17.8 | 18.9 | 19.4 | 18.6 | 20.0 | | | | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 0.763 | 0.775 | 0.694 | 0.602 | 0.701 | 0.534 |
| O2 | 1.05 | 1.02 | 0.894 | 0.838 | 0.908 | 0.752 |
| O3 | 0.781 | 0.693 | 0.674 | 0.571 | 0.561 | 0.549 |
| O4 | 0.310 | 0.307 | 0.265 | 0.238 | 0.236 | 0.212 |
| O5 | 0.344 | 0.321 | 0.297 | 0.256 | 0.251 | 0.231 |
| O6 | 0.732 | 0.714 | 0.593 | 0.576 | 0.585 | 0.541 | | 0 |
| | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 18.9 | 17.8 | 18.9 | 19.4 | 18.6 | 20.0 | | | O2 | 18.7 | 17.9 | 18.7 | 19.3 | 18.4 | 19.8 |
| --- | --- | --- | --- | --- | --- | --- |
| O3 | 17.9 | 17.2 | 17.7 | 18.3 | 17.9 | 18.8 |
| O4 | 18.6 | 17.7 | 18.5 | 19.1 | 19.0 | 19.7 |
| O5 | 18.7 | 17.6 | 18.4 | 18.9 | 19.1 | 19.5 |
| O6 | 18.8 | 17.3 | 19.0 | 19.7 | 19.3 | 20.2 | | 1 |
| | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 18.9 | 17.8 | 18.9 | 19.4 | 18.6 | 20.0 | | | O2 | 1.05 | 1.02 | 0.894 | 0.838 | 0.908 | 0.752 |
| --- | --- | --- | --- | --- | --- | --- |
| O3 | 0.781 | 0.693 | 0.674 | 0.571 | 0.561 | 0.549 |
| O4 | 0.310 | 0.307 | 0.265 | 0.238 | 0.236 | 0.212 |
| O5 | 0.344 | 0.321 | 0.297 | 0.256 | 0.251 | 0.231 |
| O6 | 0.732 | 0.714 | 0.593 | 0.576 | 0.585 | 0.541 | | 0 |
| Method | Torso | Upperarms | Lowerarms | Head | Total |
| --- | --- | --- | --- | --- | --- |
| Andrilukaetal. | 97.0 | 91.7 | 84.5 | 94.0 | 90.6 | | | Sappetal. | 100 | 88.5 | 78.0 | 87.6 | 86.8 |
| --- | --- | --- | --- | --- | --- |
| YangandRamanan | 99.8 | 95.7 | 87.5 | 95.6 | 93.6 |
| OurApproach | 100 | 97.2 | 91.3 | 99.1 | 95.7 | | 1 |
| Method | Torso | Upperarms | Lowerarms | Head | Total |
| --- | --- | --- | --- | --- | --- |
| Andrilukaetal. | 97.0 | 91.7 | 84.5 | 94.0 | 90.6 | | | Method | Torso | Head | U.Leg | L.Leg | U.Arm | L.Arm | Total |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | 88.3 | 81.8 | 64.0 | 50.6 | 42.3 | 21.3 | 52.6 |
| | 86.6 | 68.8 | 56.3 | 50.2 | 30.8 | 20.3 | 47.0 |
| | 91.5 | 85.0 | 66.8 | 54.7 | 38.3 | 23.9 | 54.4 |
| MST | 83.8 | 83.8 | 73.9 | 60.1 | 49.0 | 35.2 | 60.4 |
| OA-MST | 86.2 | 86.4 | 77.9 | 65.5 | 52.3 | 38.1 | 63.6 | | 0 |
| Method | Torso | Upperarms | Lowerarms | Head | Total |
| --- | --- | --- | --- | --- | --- |
| Andrilukaetal. | 97.0 | 91.7 | 84.5 | 94.0 | 90.6 |
| Sappetal. | 100 | 88.5 | 78.0 | 87.6 | 86.8 | | | YangandRamanan | 99.8 | 95.7 | 87.5 | 95.6 | 93.6 |
| --- | --- | --- | --- | --- | --- |
| OurApproach | 100 | 97.2 | 91.3 | 99.1 | 95.7 | | 1 |
| Method | Torso | Upperarms | Lowerarms | Head | Total |
| --- | --- | --- | --- | --- | --- |
| Andrilukaetal. | 97.0 | 91.7 | 84.5 | 94.0 | 90.6 |
| Sappetal. | 100 | 88.5 | 78.0 | 87.6 | 86.8 | | | MST | 83.8 | 83.8 | 73.9 | 60.1 | 49.0 | 35.2 | 60.4 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| OA-MST | 86.2 | 86.4 | 77.9 | 65.5 | 52.3 | 38.1 | 63.6 | | 0 |
| Stability | atopicAexistsattimetandt+1 |
| --- | --- |
| Birth | thetopicAattimet+1hasnoantecedentattimet | | | Death | thetopicAattimetdisappearsattimet+1 |
| --- | --- |
| Merging | multipletopicsattimetcombineinanewtopicAattimet+1 |
| Splitting | multipletopicsattimet+1shareanantecedentattimet | | 1 |
| Stability | atopicAexistsattimetandt+1 |
| --- | --- |
| Birth | thetopicAattimet+1hasnoantecedentattimet | | | Pattern | Total |
| --- | --- |
| (supertype)(differentiaquality) | 27 |
| (supertype)(differentiaevent) | 13 |
| (differentiaquality)(supertype) | 6 |
| (supertype)(differentiaevent)(eventlocation) | 5 |
| (supertype)(differentiaquality)(purpose) | 3 |
| (accessorydeterminer)(supertype)(differentiaevent) | 3 |
| (accessorydeterminer)(supertype)(differentiaquality) | 2 |
| (supertype)OR(differentiaquality)+ | 2 |
| (supertype)(originlocation) | 2 |
| (differentiaquality)(supertype)(differentiaquality) | 2 |
| OR(supertype)+(differentiaevent) | 2 |
| (differentiaquality)+(supertype) | 2 |
| (differentiaquality)+(supertype)(differentiaevent) | 2 |
| Other | 29 |
| Total | 100 | | 0 |
| Stability | atopicAexistsattimetandt+1 |
| --- | --- |
| Birth | thetopicAattimet+1hasnoantecedentattimet | | | Death | thetopicAattimetdisappearsattimet+1 |
| --- | --- |
| Merging | multipletopicsattimetcombineinanewtopicAattimet+1 |
| Splitting | multipletopicsattimet+1shareanantecedentattimet | | 1 |
| Stability | atopicAexistsattimetandt+1 |
| --- | --- |
| Birth | thetopicAattimet+1hasnoantecedentattimet | | | (differentiaquality)+(supertype)(differentiaevent) | 2 |
| --- | --- |
| Other | 29 |
| Total | 100 | | 0 |
| Timestamp | Downlink | Uplink | Longitude | Latitude | Accuracy | Altitude |
| --- | --- | --- | --- | --- | --- | --- |
| 100 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 | | | 101 | 566.8956 | 932.59045 | 40.459017 | -88.066069 | 13 | 189.0 |
| --- | --- | --- | --- | --- | --- | --- |
| 102 | 834.95325 | 1560.9518 | 40.459028 | -88.063833 | 11 | 195.0 |
| 103 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 |
| 104 | 878.0356 | 1117.8868 | 40.459036 | -88.062363 | 11 | 197.0 | | 1 |
| Timestamp | Downlink | Uplink | Longitude | Latitude | Accuracy | Altitude |
| --- | --- | --- | --- | --- | --- | --- |
| 100 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 | | | | Dist | StaffCost | TravelCost | CO2 | CarUse |
| --- | --- | --- | --- | --- | --- |
| Lon-1 | 204.64:206.93 | 841:974.67 | 82.54:85.79 | 133.83:163.75 | 0:0.25 |
| Lon-2 | 223.3:231.02 | 870.67:1014.67 | 89.71:103.04 | 148.94:192.85 | 0.06:0.33 |
| Lon-4 | 225.37:244.09 | 904.33:1276 | 94.63:116.74 | 158.77:194.59 | 0.04:0.33 |
| Lon-8 | 230.8:230.34 | 967.33:1376.67 | 103.5:140.1 | 159.07:240.54 | 0.04:0.35 |
| Lon-Rnd | 244.91:259.11 | 944:1140.33 | 99.48:107.4 | 155.17:216.53 | 0.04:0.33 |
| | | | | | |
| Blon-1 | 698.48:619.15 | 1987:2182.33 | 222.63:207.17 | 527.27:506.02 | 0.04:0.25 |
| Blon-2 | 729.21:644.07 | 2107.67:2385.67 | 244.54:243.55 | 584.99:581.16 | 0.07:0.32 |
| Blon-4 | 708.25:722.53 | 2183.33:2545.67 | 267.85:272.34 | 584.19:637.26 | 0.08:0.33 |
| Blon-8 | 688.94:658.52 | 2209:2772 | 272.22:311.52 | 586.81:637.5 | 0.08:0.38 |
| Blon-rnd | 730.3:666.29 | 2256:2717.67 | 251.31:263.1 | 580.16:602.47 | 0.09:0.36 | | 0 |
| Timestamp | Downlink | Uplink | Longitude | Latitude | Accuracy | Altitude |
| --- | --- | --- | --- | --- | --- | --- |
| 100 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 |
| 101 | 566.8956 | 932.59045 | 40.459017 | -88.066069 | 13 | 189.0 | | | 102 | 834.95325 | 1560.9518 | 40.459028 | -88.063833 | 11 | 195.0 |
| --- | --- | --- | --- | --- | --- | --- |
| 103 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 |
| 104 | 878.0356 | 1117.8868 | 40.459036 | -88.062363 | 11 | 197.0 | | 1 |
| Timestamp | Downlink | Uplink | Longitude | Latitude | Accuracy | Altitude |
| --- | --- | --- | --- | --- | --- | --- |
| 100 | 1192.1749 | 971.52216 | 40.459123 | -88.070278 | 14 | 193.0 |
| 101 | 566.8956 | 932.59045 | 40.459017 | -88.066069 | 13 | 189.0 | | | | | | | | |
| --- | --- | --- | --- | --- | --- |
| Blon-1 | 698.48:619.15 | 1987:2182.33 | 222.63:207.17 | 527.27:506.02 | 0.04:0.25 |
| Blon-2 | 729.21:644.07 | 2107.67:2385.67 | 244.54:243.55 | 584.99:581.16 | 0.07:0.32 |
| Blon-4 | 708.25:722.53 | 2183.33:2545.67 | 267.85:272.34 | 584.19:637.26 | 0.08:0.33 |
| Blon-8 | 688.94:658.52 | 2209:2772 | 272.22:311.52 | 586.81:637.5 | 0.08:0.38 |
| Blon-rnd | 730.3:666.29 | 2256:2717.67 | 251.31:263.1 | 580.16:602.47 | 0.09:0.36 | | 0 |
| STPair | #SeedFacts | #InferredFacts | Accuracy |
| --- | --- | --- | --- |
| (big,City) | 10,354 | 93,186 | 0.92 |
| (experienced,Athlete) | 499 | 3,488 | 0.83 | | | (cute,Animal) | 4,096 | 12,284 | 0.76 |
| --- | --- | --- | --- |
| (old,Building) | 233 | 1,398 | 0.93 |
| (popular,Film) | 272 | 1,632 | 0.87 | | 1 |
| STPair | #SeedFacts | #InferredFacts | Accuracy |
| --- | --- | --- | --- |
| (big,City) | 10,354 | 93,186 | 0.92 |
| (experienced,Athlete) | 499 | 3,488 | 0.83 | | | STPair | ClassificationModel | Accuracy |
| --- | --- | --- |
| (big,City) | DT | 0.925 |
| (experienced,Athlete) | RBF-SVM | 0.80 |
| (cute,Animal) | RBF-SVM/RF/DT | 0.685 |
| (old,Building) | RBF-SVM | 0.89 |
| (popular,Film) | DT | 0.79 | | 0 |
| STPair | #SeedFacts | #InferredFacts | Accuracy |
| --- | --- | --- | --- |
| (big,City) | 10,354 | 93,186 | 0.92 |
| (experienced,Athlete) | 499 | 3,488 | 0.83 |
| (cute,Animal) | 4,096 | 12,284 | 0.76 | | | (old,Building) | 233 | 1,398 | 0.93 |
| --- | --- | --- | --- |
| (popular,Film) | 272 | 1,632 | 0.87 | | 1 |
| STPair | #SeedFacts | #InferredFacts | Accuracy |
| --- | --- | --- | --- |
| (big,City) | 10,354 | 93,186 | 0.92 |
| (experienced,Athlete) | 499 | 3,488 | 0.83 |
| (cute,Animal) | 4,096 | 12,284 | 0.76 | | | (experienced,Athlete) | RBF-SVM | 0.80 |
| --- | --- | --- |
| (cute,Animal) | RBF-SVM/RF/DT | 0.685 |
| (old,Building) | RBF-SVM | 0.89 |
| (popular,Film) | DT | 0.79 | | 0 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prostate | 9 | 8 | 175 | 98 | 2 | 5/20 | 15/5 | 20/20 |
| dexter | 8 | 8 | 11 | 10 | 4 | 25/20 | 25/20 | 25/25 |
| arcene | 4 | 4 | 5 | 6 | 3 | 5/10 | 15/20 | 35/35 |
| dorothea | 24 | 28 | - | - | 6 | 15/15 | 40/15 | 10/10 | | | leukemia | 1014 | - | - | - | 1 | 10/20 | 20/10 | 10/10 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| breast-cancer | 8 | 6 | 10 | 7 | 4 | 40/35 | 40/25 | 35/40 | | 1 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prostate | 9 | 8 | 175 | 98 | 2 | 5/20 | 15/5 | 20/20 |
| dexter | 8 | 8 | 11 | 10 | 4 | 25/20 | 25/20 | 25/25 |
| arcene | 4 | 4 | 5 | 6 | 3 | 5/10 | 15/20 | 35/35 |
| dorothea | 24 | 28 | - | - | 6 | 15/15 | 40/15 | 10/10 | | | Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prostate | 2 | 2 | 41,568 | 54,315 | 6.37 | 2.4 | 0.09 | 4 |
| dexter | 4 | 3 | 31 | 19 | 54 | 16 | 1 | 29 |
| arcene | 3 | 3 | 16 | 15 | 20 | 1 | 0.3 | 19 |
| dorothea | 59 | 705 | - | - | 594 | 4 | 4 | 59 |
| leukemia | 10,033 | - | - | - | 5 | 2 | 0.3 | 3 |
| breast-cancer | 9 | 11 | 45 | 43 | 43.23 | 17 | 0.7 | 31 | | 0 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prostate | 9 | 8 | 175 | 98 | 2 | 5/20 | 15/5 | 20/20 |
| dexter | 8 | 8 | 11 | 10 | 4 | 25/20 | 25/20 | 25/25 |
| arcene | 4 | 4 | 5 | 6 | 3 | 5/10 | 15/20 | 35/35 | | | dorothea | 24 | 28 | - | - | 6 | 15/15 | 40/15 | 10/10 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| leukemia | 1014 | - | - | - | 1 | 10/20 | 20/10 | 10/10 |
| breast-cancer | 8 | 6 | 10 | 7 | 4 | 40/35 | 40/25 | 35/40 | | 1 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prostate | 9 | 8 | 175 | 98 | 2 | 5/20 | 15/5 | 20/20 |
| dexter | 8 | 8 | 11 | 10 | 4 | 25/20 | 25/20 | 25/25 |
| arcene | 4 | 4 | 5 | 6 | 3 | 5/10 | 15/20 | 35/35 | | | leukemia | 10,033 | - | - | - | 5 | 2 | 0.3 | 3 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| breast-cancer | 9 | 11 | 45 | 43 | 43.23 | 17 | 0.7 | 31 | | 0 |
| phrasetype | Compositional | Aspectual | Idiomatic | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| embedding | global | simplex | sense | global | simplex | sense | global | simplex | sense |
| prec@1 | 0.125 | 0.232 | 0.482 | 0.0625 | 0.0625 | 0.5 | 0.190 | 0.143 | 0.333 | | | prec@2 | 0.196 | 0.277 | 0.429 | 0.125 | 0.0625 | 0.406 | 0.238 | 0.167 | 0.429 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prec@3 | 0.220 | 0.268 | 0.417 | 0.188 | 0.042 | 0.438 | 0.190 | 0.159 | 0.381 | | 1 |
| phrasetype | Compositional | Aspectual | Idiomatic | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| embedding | global | simplex | sense | global | simplex | sense | global | simplex | sense |
| prec@1 | 0.125 | 0.232 | 0.482 | 0.0625 | 0.0625 | 0.5 | 0.190 | 0.143 | 0.333 | | | | Max.length(words) | | | |
| --- | --- | --- | --- | --- |
| Preferencemethod | 8 | 12 | 16 | ∞ |
| (1-best) | 24.3 | 26.0 | 27.5 | 28.8 |
| highest-in-coverage | 20.4 | 21.5 | 23.7 | 25.3 |
| recognizer+N-gramKSs | 20.4 | 22.5 | 23.8 | 25.2 |
| N-gram/highest-in-coverage | 19.0 | 20.5 | 22.6 | 24.1 |
| recognizer+linguisticKSs | 17.6 | 19.6 | 21.7 | 23.5 |
| allavailableKSs | 17.6 | 19.6 | 21.5 | 22.8 |
| (lowestWEin10-best) | 11.3 | 12.0 | 13.0 | 14.0 |
| (#utterances) | 506 | 818 | 936 | 1001 | | 0 |
| phrasetype | Compositional | Aspectual | Idiomatic | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| embedding | global | simplex | sense | global | simplex | sense | global | simplex | sense |
| prec@1 | 0.125 | 0.232 | 0.482 | 0.0625 | 0.0625 | 0.5 | 0.190 | 0.143 | 0.333 | | | prec@2 | 0.196 | 0.277 | 0.429 | 0.125 | 0.0625 | 0.406 | 0.238 | 0.167 | 0.429 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| prec@3 | 0.220 | 0.268 | 0.417 | 0.188 | 0.042 | 0.438 | 0.190 | 0.159 | 0.381 | | 1 |
| phrasetype | Compositional | Aspectual | Idiomatic | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| embedding | global | simplex | sense | global | simplex | sense | global | simplex | sense |
| prec@1 | 0.125 | 0.232 | 0.482 | 0.0625 | 0.0625 | 0.5 | 0.190 | 0.143 | 0.333 | | | highest-in-coverage | 20.4 | 21.5 | 23.7 | 25.3 |
| --- | --- | --- | --- | --- |
| recognizer+N-gramKSs | 20.4 | 22.5 | 23.8 | 25.2 |
| N-gram/highest-in-coverage | 19.0 | 20.5 | 22.6 | 24.1 |
| recognizer+linguisticKSs | 17.6 | 19.6 | 21.7 | 23.5 |
| allavailableKSs | 17.6 | 19.6 | 21.5 | 22.8 |
| (lowestWEin10-best) | 11.3 | 12.0 | 13.0 | 14.0 |
| (#utterances) | 506 | 818 | 936 | 1001 | | 0 |
| Role | ARG | CVAG |
| --- | --- | --- |
| Leader | No | Yes |
| Analyzer | No | Yes |
| Designer | No | Yes | | | Author | No | Yes |
| --- | --- | --- |
| Timekeeper | No | Yes |
| Explainer | Yes | Yes |
| Recorder | Yes | No |
| Gate-keeper | Yes | No |
| Directiongiver | Yes | No |
| Clarifier/paraphraser | Yes | Yes(*) |
| Summarizer | Yes | No |
| Accuracycoach | Yes | Yes(**) |
| Understandingchecker | Yes | No |
| Elaborator | Yes | No |
| Perspective-takingroles | Yes | No |
| Ideacriticizer | Yes | No |
| Justificationasker | Yes | No |
| Differentiator | Yes | No |
| Integrator | Yes | Yes |
| Extender | Yes | No |
| Prober | Yes | No | | 1 |
| Role | ARG | CVAG |
| --- | --- | --- |
| Leader | No | Yes |
| Analyzer | No | Yes |
| Designer | No | Yes | | | # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence |
| 5 | Last | Whetherwexistsinthelastsentence |
| 6 | NE | Whetherwisanamedentity(NE) |
| 7 | NEFirst | WhetherwisNEinthefirstsentence |
| 8 | NELast | WhetherwisNEinthelastsentence |
| 9 | POS | Partofspeechofw | | 0 |
| Role | ARG | CVAG |
| --- | --- | --- |
| Leader | No | Yes |
| Analyzer | No | Yes |
| Designer | No | Yes |
| Author | No | Yes |
| Timekeeper | No | Yes |
| Explainer | Yes | Yes |
| Recorder | Yes | No |
| Gate-keeper | Yes | No |
| Directiongiver | Yes | No | | | Clarifier/paraphraser | Yes | Yes(*) |
| --- | --- | --- |
| Summarizer | Yes | No |
| Accuracycoach | Yes | Yes(**) |
| Understandingchecker | Yes | No |
| Elaborator | Yes | No |
| Perspective-takingroles | Yes | No |
| Ideacriticizer | Yes | No |
| Justificationasker | Yes | No |
| Differentiator | Yes | No |
| Integrator | Yes | Yes |
| Extender | Yes | No |
| Prober | Yes | No | | 1 |
| Role | ARG | CVAG |
| --- | --- | --- |
| Leader | No | Yes |
| Analyzer | No | Yes |
| Designer | No | Yes |
| Author | No | Yes |
| Timekeeper | No | Yes |
| Explainer | Yes | Yes |
| Recorder | Yes | No |
| Gate-keeper | Yes | No |
| Directiongiver | Yes | No | | | 8 | NELast | WhetherwisNEinthelastsentence |
| --- | --- | --- |
| 9 | POS | Partofspeechofw | | 0 |
| Method | CPUTime(seconds) | Numberofiterations | (cid:107)x(cid:107)1 |
| --- | --- | --- | --- |
| FISTA | 1690 | 554 | 3.98 | | | APCG | 680 | 68,363(blocksize10) | 6.67 |
| --- | --- | --- | --- |
| SVRG | ≥10,000 | ≥93(epochlength17,648) | 5.19 |
| MAGMA | 526 | 144fineand120coarse | 3.09 | | 1 |
| Method | CPUTime(seconds) | Numberofiterations | (cid:107)x(cid:107)1 |
| --- | --- | --- | --- |
| FISTA | 1690 | 554 | 3.98 | | | | NoFaults | OneInjectedFault | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Numberof<br>Processes | Partial-Order<br>Methods | Computation<br>Slicing | Partial-Order<br>Methods | Computation<br>Slicing | | | | |
| n | T | M | T | M | T | M | T | M |
| 6 | 69 | 0.62 | 356 | 1.21 | 46 | 0.41 | 366 | 1.38 |
| 7 | 163 | 1.11 | 609 | 1.34 | 110 | 0.81 | 584 | 1.41 |
| 8 | 367 | 2.06 | 901 | 1.54 | 312 | 1.79 | 908 | 1.61 |
| 9 | 832 | 4.37 | 1243 | 1.70 | 586 | 3.05 | 1207 | 1.77 |
| 10 | 1516 | 7.26 | 1734 | 1.81 | 1115 | 5.54 | 1700 | 2.00 |
| 11 | 2992 | 13.14 | 2147 | 1.93 | 2087 | 9.50 | 2128 | 2.27 |
| 12 | 4997 | 21.56 | 2849 | 2.16 | 3510 | 14.13 | 2765 | 2.43 | | 0 |
| Method | CPUTime(seconds) | Numberofiterations | (cid:107)x(cid:107)1 |
| --- | --- | --- | --- |
| FISTA | 1690 | 554 | 3.98 |
| APCG | 680 | 68,363(blocksize10) | 6.67 | | | SVRG | ≥10,000 | ≥93(epochlength17,648) | 5.19 |
| --- | --- | --- | --- |
| MAGMA | 526 | 144fineand120coarse | 3.09 | | 1 |
| Method | CPUTime(seconds) | Numberofiterations | (cid:107)x(cid:107)1 |
| --- | --- | --- | --- |
| FISTA | 1690 | 554 | 3.98 |
| APCG | 680 | 68,363(blocksize10) | 6.67 | | | 8 | 367 | 2.06 | 901 | 1.54 | 312 | 1.79 | 908 | 1.61 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 9 | 832 | 4.37 | 1243 | 1.70 | 586 | 3.05 | 1207 | 1.77 |
| 10 | 1516 | 7.26 | 1734 | 1.81 | 1115 | 5.54 | 1700 | 2.00 |
| 11 | 2992 | 13.14 | 2147 | 1.93 | 2087 | 9.50 | 2128 | 2.27 |
| 12 | 4997 | 21.56 | 2849 | 2.16 | 3510 | 14.13 | 2765 | 2.43 | | 0 |
| K=1000 | C2F | C2F+wt |
| --- | --- | --- |
| 0 | 82.25 | 86.78 |
| 1000 | 80.23 | 83.95 |
| 10,000 | 77.36 | 79.30 | | | 100,000 | 71.64 | 72.73 |
| --- | --- | --- |
| 500,000 | 68.39 | 69.41 |
| 1,000,000 | 67.26 | 69.15 | | 1 |
| K=1000 | C2F | C2F+wt |
| --- | --- | --- |
| 0 | 82.25 | 86.78 |
| 1000 | 80.23 | 83.95 |
| 10,000 | 77.36 | 79.30 | | | τ | 0.00 | 0.05 | 0.10 | 0.15 | 0.20 | 0.25 |
| --- | --- | --- | --- | --- | --- | --- |
| DE(c,c)d | 0.000 | 0.050 | 0.100 | 0.150 | 0.200 | 0.231 |
| DE(c,c)i | 0.000 | 0.050 | 0.055 | 0.055 | 0.055 | 0.055 |
| SFD | 43490 | 24602 | 14370 | 9041 | 3444 | 0 |
| KTD | 123626 | 72938 | 45636 | 28652 | 11054 | 0 | | 0 |
| K=1000 | C2F | C2F+wt |
| --- | --- | --- |
| 0 | 82.25 | 86.78 | | | 1000 | 80.23 | 83.95 |
| --- | --- | --- |
| 10,000 | 77.36 | 79.30 |
| 100,000 | 71.64 | 72.73 |
| 500,000 | 68.39 | 69.41 |
| 1,000,000 | 67.26 | 69.15 | | 1 |
| K=1000 | C2F | C2F+wt |
| --- | --- | --- |
| 0 | 82.25 | 86.78 | | | SFD | 43490 | 24602 | 14370 | 9041 | 3444 | 0 |
| --- | --- | --- | --- | --- | --- | --- |
| KTD | 123626 | 72938 | 45636 | 28652 | 11054 | 0 | | 0 |
| Metric(avg.) | NAMIC | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| | | | | | | | | | | PSNR(dB) | 24.36 | 26.51 | 27.14 | 27.30 | 27.26 | 27.81 | 29.04 | 30.35 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SSIM | 0.8771 | 0.8874 | 0.8934 | 0.8983 | 0.9166 | 0.9130 | 0.9173 | 0.9270 | | 1 |
| Metric(avg.) | NAMIC | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| | | | | | | | | | | Metric(avg.) | NAMIC | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | | | | |
| | | | | | | |
| PSNR | 24.98 | 27.22 | 29.83 | 27.13 | 28.95 | 32.03 |
| SSIM | 0.8821 | 0.8981 | 0.9013 | 0.9198 | 0.9273 | 0.9301 | | 0 |
| Metric(avg.) | NAMIC |
| --- | --- |
| | | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PSNR(dB) | 24.36 | 26.51 | 27.14 | 27.30 | 27.26 | 27.81 | 29.04 | 30.35 |
| SSIM | 0.8771 | 0.8874 | 0.8934 | 0.8983 | 0.9166 | 0.9130 | 0.9173 | 0.9270 | | 1 |
| Metric(avg.) | NAMIC |
| --- | --- |
| | | | | PSNR | 24.98 | 27.22 | 29.83 | 27.13 | 28.95 | 32.03 |
| --- | --- | --- | --- | --- | --- | --- |
| SSIM | 0.8821 | 0.8981 | 0.9013 | 0.9198 | 0.9273 | 0.9301 | | 0 |
| Synchronous | Asynchronous | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Machine | DSSize | STEP01 | STEP2 | Time | STEP1 | STEP2 | Time |
| M1 | 10000 | 21270 | 1104 | 22374 | 21270 | 554 | 21824 | | | M2 | 2500 | 1060 | 20862 | 21922 | 1060 | 2515 | 3575 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| M3 | 3275 | 5093 | 16930 | 22023 | 5093 | 2017 | 7110 |
| M4 | 5000 | 4592 | 17644 | 22236 | 4591 | 2620 | 7211 |
| M5 | 1666 | 227 | 21642 | 21869 | 227 | 391 | 618 |
| M6 | 2000 | 292 | 21736 | 22028 | 292 | 416 | 708 |
| M7 | 5000 | 7520 | 14665 | 22185 | 7515 | 13949 | 21464 |
| M8 | 1500 | 200 | 21842 | 22042 | 195 | 4605 | 4800 |
| TotalExec-Time | 22374 | TotalExec-Time | 21824 | | | | | | 1 |
| Synchronous | Asynchronous | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Machine | DSSize | STEP01 | STEP2 | Time | STEP1 | STEP2 | Time |
| M1 | 10000 | 21270 | 1104 | 22374 | 21270 | 554 | 21824 | | | Synchronous | Asynchronous | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Machine | DSSize | STEP1 | STEP2 | Time | STEP1 | STEP2 | Time |
| M1 | 10000 | 21270 | 35978 | 57248 | 21270 | 905 | 22175 |
| M2 | 10000 | 21590 | 34869 | 56459 | 21590 | 11513 | 33103 |
| M3 | 10000 | 53005 | 3008 | 56013 | 53005 | 3292 | 56297 |
| M4 | 10000 | 32424 | 24691 | 57115 | 32424 | 6996 | 39420 |
| M5 | 10000 | 17364 | 38493 | 55857 | 17364 | 4612 | 21976 |
| M6 | 10000 | 15841 | 41237 | 57078 | 15841 | 2066 | 17907 |
| M7 | 10000 | 38732 | 18483 | 57215 | 38727 | 18459 | 57186 |
| M8 | 1250 | 185 | 56915 | 57100 | 184 | 16077 | 16261 |
| TotalExec-Time | 57248 | TotalExec-Time | 57186 | | | | | | 0 |
| Synchronous | Asynchronous | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Machine | DSSize | STEP01 | STEP2 | Time | STEP1 | STEP2 | Time |
| M1 | 10000 | 21270 | 1104 | 22374 | 21270 | 554 | 21824 |
| M2 | 2500 | 1060 | 20862 | 21922 | 1060 | 2515 | 3575 |
| M3 | 3275 | 5093 | 16930 | 22023 | 5093 | 2017 | 7110 |
| M4 | 5000 | 4592 | 17644 | 22236 | 4591 | 2620 | 7211 |
| M5 | 1666 | 227 | 21642 | 21869 | 227 | 391 | 618 |
| M6 | 2000 | 292 | 21736 | 22028 | 292 | 416 | 708 |
| M7 | 5000 | 7520 | 14665 | 22185 | 7515 | 13949 | 21464 | | | M8 | 1500 | 200 | 21842 | 22042 | 195 | 4605 | 4800 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| TotalExec-Time | 22374 | TotalExec-Time | 21824 | | | | | | 1 |
| Synchronous | Asynchronous | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Machine | DSSize | STEP01 | STEP2 | Time | STEP1 | STEP2 | Time |
| M1 | 10000 | 21270 | 1104 | 22374 | 21270 | 554 | 21824 |
| M2 | 2500 | 1060 | 20862 | 21922 | 1060 | 2515 | 3575 |
| M3 | 3275 | 5093 | 16930 | 22023 | 5093 | 2017 | 7110 |
| M4 | 5000 | 4592 | 17644 | 22236 | 4591 | 2620 | 7211 |
| M5 | 1666 | 227 | 21642 | 21869 | 227 | 391 | 618 |
| M6 | 2000 | 292 | 21736 | 22028 | 292 | 416 | 708 |
| M7 | 5000 | 7520 | 14665 | 22185 | 7515 | 13949 | 21464 | | | M4 | 10000 | 32424 | 24691 | 57115 | 32424 | 6996 | 39420 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| M5 | 10000 | 17364 | 38493 | 55857 | 17364 | 4612 | 21976 |
| M6 | 10000 | 15841 | 41237 | 57078 | 15841 | 2066 | 17907 |
| M7 | 10000 | 38732 | 18483 | 57215 | 38727 | 18459 | 57186 |
| M8 | 1250 | 185 | 56915 | 57100 | 184 | 16077 | 16261 |
| TotalExec-Time | 57248 | TotalExec-Time | 57186 | | | | | | 0 |
| Size | Diameter | Average | Median | Localest. | Nr.ofconf. |
| --- | --- | --- | --- | --- | --- |
| 1×1 | 4 | 2.17 | 2 | 9 | 24 |
| 2×1 | 7 | 4.44 | 5 | 18 | 576 |
| 3×1 | 10 | 6.59 | 7 | 27 | 13824 |
| 4×1 | 12 | 8.59 | 9 | 36 | 331776 |
| 2×2 | 12 | 7.82 | 8 | 35 | 16588 | | | 5×1 | 15 | 10.69 | 11 | 45 | 7962624 |
| --- | --- | --- | --- | --- | --- |
| 6×1 | 17 | 12.65 | 13 | 54 | 191102976 |
| 3×2 | 14 | 10.54 | 11 | 52 | 47775744 | | 1 |
| Size | Diameter | Average | Median | Localest. | Nr.ofconf. |
| --- | --- | --- | --- | --- | --- |
| 1×1 | 4 | 2.17 | 2 | 9 | 24 |
| 2×1 | 7 | 4.44 | 5 | 18 | 576 |
| 3×1 | 10 | 6.59 | 7 | 27 | 13824 |
| 4×1 | 12 | 8.59 | 9 | 36 | 331776 |
| 2×2 | 12 | 7.82 | 8 | 35 | 16588 | | | 0 | 10 | 20 | 30 | 40 | 50 | 60 |
| --- | --- | --- | --- | --- | --- | --- |
| 9.3 | 7.6 | 5.9 | 4.3 | 3.0 | 2.0 | 1.2 |
| 38.2 | 31.1 | 24.4 | 18.3 | 13.1 | 8.8 | 5.5 |
| 86.7 | 70.4 | 55.2 | 41.4 | 29.7 | 19.9 | 12.4 |
| 155.4 | 125.9 | 98.9 | 74.4 | 53.5 | 36.1 | 22.5 |
| 326.0 | 264.5 | 207.6 | 156.2 | 111.9 | 75.7 | 47.1 | | 0 |
| Size | Diameter | Average | Median | Localest. | Nr.ofconf. |
| --- | --- | --- | --- | --- | --- |
| 1×1 | 4 | 2.17 | 2 | 9 | 24 |
| 2×1 | 7 | 4.44 | 5 | 18 | 576 |
| 3×1 | 10 | 6.59 | 7 | 27 | 13824 |
| 4×1 | 12 | 8.59 | 9 | 36 | 331776 | | | 2×2 | 12 | 7.82 | 8 | 35 | 16588 |
| --- | --- | --- | --- | --- | --- |
| 5×1 | 15 | 10.69 | 11 | 45 | 7962624 |
| 6×1 | 17 | 12.65 | 13 | 54 | 191102976 |
| 3×2 | 14 | 10.54 | 11 | 52 | 47775744 | | 1 |
| Size | Diameter | Average | Median | Localest. | Nr.ofconf. |
| --- | --- | --- | --- | --- | --- |
| 1×1 | 4 | 2.17 | 2 | 9 | 24 |
| 2×1 | 7 | 4.44 | 5 | 18 | 576 |
| 3×1 | 10 | 6.59 | 7 | 27 | 13824 |
| 4×1 | 12 | 8.59 | 9 | 36 | 331776 | | | 38.2 | 31.1 | 24.4 | 18.3 | 13.1 | 8.8 | 5.5 |
| --- | --- | --- | --- | --- | --- | --- |
| 86.7 | 70.4 | 55.2 | 41.4 | 29.7 | 19.9 | 12.4 |
| 155.4 | 125.9 | 98.9 | 74.4 | 53.5 | 36.1 | 22.5 |
| 326.0 | 264.5 | 207.6 | 156.2 | 111.9 | 75.7 | 47.1 | | 0 |
| Phase | Step | RT(sec) |
| --- | --- | --- |
| LoadTime | LoadingModel | 30.50 |
| LoadTime | UDF:EmbedTuples | 55.00 |
| LoadTime | UDF:EmbedSentences | 150.00 |
| LoadTime | CreateIndexforTuples | 0.04 |
| LoadTime | CreateIndexforSentences | 3.07 |
| LoadTime | Sumoverallsteps | 208.1 | | | QueryTime | CrossJoinTop10 | 115.9 |
| --- | --- | --- |
| QueryTime | UDF:QueryNNTop10Sent. | 9.60 |
| QueryTime | UDF:QueryNNTop10Tuples | 29.15 | | 1 |
| Phase | Step | RT(sec) |
| --- | --- | --- |
| LoadTime | LoadingModel | 30.50 |
| LoadTime | UDF:EmbedTuples | 55.00 |
| LoadTime | UDF:EmbedSentences | 150.00 |
| LoadTime | CreateIndexforTuples | 0.04 |
| LoadTime | CreateIndexforSentences | 3.07 |
| LoadTime | Sumoverallsteps | 208.1 | | | Parameter | Setting |
| --- | --- |
| Spacedomain(m×m) | 10,000×10,000 |
| Numberofobjects | 100K,200K,...,500K |
| Querywindowsize(m×m) | 200×200,400×400,...,1000×1000 |
| kNN-k | 10,20,30,...,50 |
| Querypredicttime(ts) | 0,30,60,...,120 |
| Nodesize(byte) | 1K,2K,4K,···,16K |
| Datasets | SEO,LD,BOS,SZ | | 0 |
| Phase | Step | RT(sec) |
| --- | --- | --- |
| LoadTime | LoadingModel | 30.50 |
| LoadTime | UDF:EmbedTuples | 55.00 |
| LoadTime | UDF:EmbedSentences | 150.00 |
| LoadTime | CreateIndexforTuples | 0.04 | | | LoadTime | CreateIndexforSentences | 3.07 |
| --- | --- | --- |
| LoadTime | Sumoverallsteps | 208.1 |
| QueryTime | CrossJoinTop10 | 115.9 |
| QueryTime | UDF:QueryNNTop10Sent. | 9.60 |
| QueryTime | UDF:QueryNNTop10Tuples | 29.15 | | 1 |
| Phase | Step | RT(sec) |
| --- | --- | --- |
| LoadTime | LoadingModel | 30.50 |
| LoadTime | UDF:EmbedTuples | 55.00 |
| LoadTime | UDF:EmbedSentences | 150.00 |
| LoadTime | CreateIndexforTuples | 0.04 | | | Numberofobjects | 100K,200K,...,500K |
| --- | --- |
| Querywindowsize(m×m) | 200×200,400×400,...,1000×1000 |
| kNN-k | 10,20,30,...,50 |
| Querypredicttime(ts) | 0,30,60,...,120 |
| Nodesize(byte) | 1K,2K,4K,···,16K |
| Datasets | SEO,LD,BOS,SZ | | 0 |
| Images |
| --- |
| 400,000 |
| 87,577 | | | 121,450 |
| --- |
| 191,463 |
| 403,398 |
| 925,327 | | 1 |
| Images |
| --- |
| 400,000 |
| 87,577 | | | ProbeSet | Gallery |
| --- | --- |
| 7,745 | 100 |
| 12,529 | 200 |
| 18,644 | 400 |
| 22,395 | 600 |
| 24,555 | 800 |
| 25,582 | 1,000 |
| 26,078 | 1,200 |
| 26,478 | 1,400 | | 0 |
| Images |
| --- |
| 400,000 |
| 87,577 |
| 121,450 |
| 191,463 | | | 403,398 |
| --- |
| 925,327 | | 1 |
| Images |
| --- |
| 400,000 |
| 87,577 |
| 121,450 |
| 191,463 | | | 18,644 | 400 |
| --- | --- |
| 22,395 | 600 |
| 24,555 | 800 |
| 25,582 | 1,000 |
| 26,078 | 1,200 |
| 26,478 | 1,400 | | 0 |
| Algorithm | MR=0.25 | MR=0.10 | MR=0.04 | MR=0.01 |
| --- | --- | --- | --- | --- |
| TVAL3 | 2.943 | 3.223 | 3.467 | 7.790 | | | NLR-CS | 314.852 | 305.703 | 300.666 | 314.176 |
| --- | --- | --- | --- | --- |
| D-AMP | 27.764 | 31.849 | 34.207 | 54.643 |
| ReconNet(CPU) | 0.5249 | 0.5258 | 0.5284 | 0.5193 |
| ReconNet(GPU) | 0.0213 | 0.0195 | 0.0192 | 0.0244 |
| SDA(GPU) | 0.0042 | 0.0029 | 0.0025 | 0.0045 | | 1 |
| Algorithm | MR=0.25 | MR=0.10 | MR=0.04 | MR=0.01 |
| --- | --- | --- | --- | --- |
| TVAL3 | 2.943 | 3.223 | 3.467 | 7.790 | | | R | Optimalvalue | iter | CPU |
| --- | --- | --- | --- |
| 0.0001 | 0.000186 | 2 | 0.235 |
| 0.0002 | 0.000189 | 2 | 0.234 |
| 0.0003 | 0.000193 | 2 | 0.218 |
| 0.0004 | 0.000182 | 3 | 0.266 |
| 0.0005 | 0.000174 | 3 | 0.266 |
| 0.0006 | 0.000173 | 4 | 0.312 |
| 0.0007 | 0.000170 | 4 | 0.313 |
| 0.0008 | 0.000167 | 3 | 0.266 |
| 0.0009 | 0.000167 | 4 | 0.313 |
| 0.001 | 0.000167 | 4 | 0.312 |
| 0.002 | 0.000156 | 2 | 0.219 |
| 0.003 | 0.000159 | 2 | 0.234 |
| 0.004 | 0.000207 | 2 | 0.203 | | 0 |
| Algorithm | MR=0.25 | MR=0.10 | MR=0.04 | MR=0.01 |
| --- | --- | --- | --- | --- |
| TVAL3 | 2.943 | 3.223 | 3.467 | 7.790 |
| NLR-CS | 314.852 | 305.703 | 300.666 | 314.176 |
| D-AMP | 27.764 | 31.849 | 34.207 | 54.643 |
| ReconNet(CPU) | 0.5249 | 0.5258 | 0.5284 | 0.5193 | | | ReconNet(GPU) | 0.0213 | 0.0195 | 0.0192 | 0.0244 |
| --- | --- | --- | --- | --- |
| SDA(GPU) | 0.0042 | 0.0029 | 0.0025 | 0.0045 | | 1 |
| Algorithm | MR=0.25 | MR=0.10 | MR=0.04 | MR=0.01 |
| --- | --- | --- | --- | --- |
| TVAL3 | 2.943 | 3.223 | 3.467 | 7.790 |
| NLR-CS | 314.852 | 305.703 | 300.666 | 314.176 |
| D-AMP | 27.764 | 31.849 | 34.207 | 54.643 |
| ReconNet(CPU) | 0.5249 | 0.5258 | 0.5284 | 0.5193 | | | 0.0006 | 0.000173 | 4 | 0.312 |
| --- | --- | --- | --- |
| 0.0007 | 0.000170 | 4 | 0.313 |
| 0.0008 | 0.000167 | 3 | 0.266 |
| 0.0009 | 0.000167 | 4 | 0.313 |
| 0.001 | 0.000167 | 4 | 0.312 |
| 0.002 | 0.000156 | 2 | 0.219 |
| 0.003 | 0.000159 | 2 | 0.234 |
| 0.004 | 0.000207 | 2 | 0.203 | | 0 |
| Tribune | NYPost | Suntimes | Freep | Techweb | CleanEval | Myriad40 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.871 | 0.975 | 0.536 | 0.846 | 0.814 | 0.725 | 0.784 | | | 0.816 | 0.975 | 0.536 | 0.846 | 0.814 | 0.702 | 0.784 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.657 | 0.234 | 0.405 | 0.307 | 0.387 | 0.567 | 0.530 |
| 0.546 | 0.262 | 0.420 | 0.319 | 0.394 | 0.404 | 0.515 |
| 0.871 | 0.981 | 0.899 | 0.845 | 0.880 | 0.767 | 0.807 |
| 0.871 | 0.981 | 0.922 | 0.858 | 0.888 | 0.825 | 0.828 | | 1 |
| Tribune | NYPost | Suntimes | Freep | Techweb | CleanEval | Myriad40 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.871 | 0.975 | 0.536 | 0.846 | 0.814 | 0.725 | 0.784 | | | Tribune | NYPost | Suntimes | Freep | Techweb | CleanEval | Myriad40 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.856 | 0.949 | 0.518 | 0.834 | 0.757 | 0.725 | 0.778 |
| 0.794 | 0.949 | 0.518 | 0.834 | 0.757 | 0.673 | 0.778 |
| 0.771 | 0.417 | 0.591 | 0.608 | 0.603 | 0.662 | 0.643 |
| 0.690 | 0.439 | 0.590 | 0.627 | 0.609 | 0.508 | 0.632 |
| 0.855 | 0.964 | 0.799 | 0.836 | 0.828 | 0.743 | 0.804 |
| 0.855 | 0.964 | 0.812 | 0.846 | 0.838 | 0.802 | 0.831 | | 0 |
| Tribune | NYPost | Suntimes | Freep | Techweb | CleanEval | Myriad40 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.871 | 0.975 | 0.536 | 0.846 | 0.814 | 0.725 | 0.784 | | | 0.816 | 0.975 | 0.536 | 0.846 | 0.814 | 0.702 | 0.784 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.657 | 0.234 | 0.405 | 0.307 | 0.387 | 0.567 | 0.530 |
| 0.546 | 0.262 | 0.420 | 0.319 | 0.394 | 0.404 | 0.515 |
| 0.871 | 0.981 | 0.899 | 0.845 | 0.880 | 0.767 | 0.807 |
| 0.871 | 0.981 | 0.922 | 0.858 | 0.888 | 0.825 | 0.828 | | 1 |
| Tribune | NYPost | Suntimes | Freep | Techweb | CleanEval | Myriad40 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.871 | 0.975 | 0.536 | 0.846 | 0.814 | 0.725 | 0.784 | | | 0.794 | 0.949 | 0.518 | 0.834 | 0.757 | 0.673 | 0.778 |
| --- | --- | --- | --- | --- | --- | --- |
| 0.771 | 0.417 | 0.591 | 0.608 | 0.603 | 0.662 | 0.643 |
| 0.690 | 0.439 | 0.590 | 0.627 | 0.609 | 0.508 | 0.632 |
| 0.855 | 0.964 | 0.799 | 0.836 | 0.828 | 0.743 | 0.804 |
| 0.855 | 0.964 | 0.812 | 0.846 | 0.838 | 0.802 | 0.831 | | 0 |
| Algorithm | Symm | Asymm | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.9037 | 0.8991 | 7.0246 | 0.8769 | 0.8755 | 5.8162 | | | MS-SSIM | 0.8901 | 0.8681 | 21.2322 | 0.8423 | 0.7785 | 15.1681 |
| --- | --- | --- | --- | --- | --- | --- |
| SBIQE | 0.0006 | 0.0027 | 25.4484 | 0.0021 | 0.0051 | 12.0123 |
| BRISQUE | 0.7829 | 0.7859 | 15.8298 | 0.5411 | 0.5303 | 10.1719 |
| NIQE | 0.8499 | 0.8705 | 13.4076 | 0.6835 | 0.6929 | 8.8334 |
| STMAD | 0.7815 | 0.8000 | 10.2358 | 0.6534 | 0.6010 | 9.1614 |
| Chenetal. | 0.9435 | 0.9182 | 5.4346 | 0.8370 | 0.8376 | 6.6218 |
| STRIQE | 0.8275 | 0.8017 | 9.2105 | 0.7559 | 0.7492 | 7.9321 |
| VQUEMODES(NIQE) | 0.9285 | 0.9236 | 3.9852 | 0.8955 | 0.8490 | 6.9563 | | 1 |
| Algorithm | Symm | Asymm | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.9037 | 0.8991 | 7.0246 | 0.8769 | 0.8755 | 5.8162 | | | Algorithm | IRCCYNDatabase | LFOVIADatabase | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.6359 | 0.2465 | 1.0264 | 0.8816 | 0.8828 | 6.1104 |
| MS-SSIM | 0.9100 | 0.8534 | 0.6512 | 0.8172 | 0.7888 | 8.9467 |
| SBIQE | 0.0081 | 0.0054 | 1.2712 | 0.0010 | 0.0043 | 16.0311 |
| BRISQUE | 0.7535 | 0.8145 | 0.6535 | 0.6182 | 0.6000 | 12.6001 |
| NIQE | 0.5729 | 0.5664 | 0.8464 | 0.7206 | 0.7376 | 11.1138 |
| STMAD | 0.6400 | 0.3495 | 0.9518 | 0.6802 | 0.6014 | 9.4918 |
| FLOSIM | 0.9178 | 0.9111 | 0.4918 | - | - | - |
| Chenetal. | 0.7886 | 0.7861 | 0.7464 | 0.8573 | 0.8588 | 6.6655 |
| STRIQE | 0.7931 | 0.6400 | 0.7544 | 0.7543 | 0.7485 | 8.5011 |
| VQUEMODES(NIQE) | 0.9697 | 0.9637 | 0.2635 | 0.8943 | 0.8890 | 5.9124 | | 0 |
| Algorithm | Symm | Asymm | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.9037 | 0.8991 | 7.0246 | 0.8769 | 0.8755 | 5.8162 |
| MS-SSIM | 0.8901 | 0.8681 | 21.2322 | 0.8423 | 0.7785 | 15.1681 |
| SBIQE | 0.0006 | 0.0027 | 25.4484 | 0.0021 | 0.0051 | 12.0123 |
| BRISQUE | 0.7829 | 0.7859 | 15.8298 | 0.5411 | 0.5303 | 10.1719 | | | NIQE | 0.8499 | 0.8705 | 13.4076 | 0.6835 | 0.6929 | 8.8334 |
| --- | --- | --- | --- | --- | --- | --- |
| STMAD | 0.7815 | 0.8000 | 10.2358 | 0.6534 | 0.6010 | 9.1614 |
| Chenetal. | 0.9435 | 0.9182 | 5.4346 | 0.8370 | 0.8376 | 6.6218 |
| STRIQE | 0.8275 | 0.8017 | 9.2105 | 0.7559 | 0.7492 | 7.9321 |
| VQUEMODES(NIQE) | 0.9285 | 0.9236 | 3.9852 | 0.8955 | 0.8490 | 6.9563 | | 1 |
| Algorithm | Symm | Asymm | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | |
| SSIM | 0.9037 | 0.8991 | 7.0246 | 0.8769 | 0.8755 | 5.8162 |
| MS-SSIM | 0.8901 | 0.8681 | 21.2322 | 0.8423 | 0.7785 | 15.1681 |
| SBIQE | 0.0006 | 0.0027 | 25.4484 | 0.0021 | 0.0051 | 12.0123 |
| BRISQUE | 0.7829 | 0.7859 | 15.8298 | 0.5411 | 0.5303 | 10.1719 | | | Chenetal. | 0.7886 | 0.7861 | 0.7464 | 0.8573 | 0.8588 | 6.6655 |
| --- | --- | --- | --- | --- | --- | --- |
| STRIQE | 0.7931 | 0.6400 | 0.7544 | 0.7543 | 0.7485 | 8.5011 |
| VQUEMODES(NIQE) | 0.9697 | 0.9637 | 0.2635 | 0.8943 | 0.8890 | 5.9124 | | 0 |
| Supporters | No.ofLabeledUsers |
| --- | --- |
| pro-Erdogan | 1,777 | | | anti-Erdoganw/outpartyaffiliation | 2,134 |
| --- | --- |
| pro-CHP | 833 |
| pro-IYIParty | 900 |
| pro-HDP | 357 | | 1 |
| Supporters | No.ofLabeledUsers |
| --- | --- |
| pro-Erdogan | 1,777 | | | Protestors | H | I-POMDP | Many-Agent | Exp.Value |
| --- | --- | --- | --- | --- |
| 2 | 2<br>3 | 1s<br>19s | 0.55s<br>17s | 77.42<br>222.42 |
| 3 | 2<br>3 | 3s<br>38s | 0.56s<br>17s | 77.34<br>222.32 |
| 4 | 2<br>3 | 39s<br>223s | 0.57s<br>17s | 76.96<br>221.87 |
| 5 | 2<br>3 | 603s<br>2,480s | 0.60s<br>18s | 76.88<br>221.77 | | 0 |
| Supporters | No.ofLabeledUsers |
| --- | --- |
| pro-Erdogan | 1,777 |
| anti-Erdoganw/outpartyaffiliation | 2,134 | | | pro-CHP | 833 |
| --- | --- |
| pro-IYIParty | 900 |
| pro-HDP | 357 | | 1 |
| Supporters | No.ofLabeledUsers |
| --- | --- |
| pro-Erdogan | 1,777 |
| anti-Erdoganw/outpartyaffiliation | 2,134 | | | 3 | 2<br>3 | 3s<br>38s | 0.56s<br>17s | 77.34<br>222.32 |
| --- | --- | --- | --- | --- |
| 4 | 2<br>3 | 39s<br>223s | 0.57s<br>17s | 76.96<br>221.87 |
| 5 | 2<br>3 | 603s<br>2,480s | 0.60s<br>18s | 76.88<br>221.77 | | 0 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 150000 | 25000 | 10000 | 5000 |
| 450000 | 15000 | 20000 | 30000 |
| 35000 | 35000 | 5000 | 10000 |
| 45000 | 20000 | 30000 | 80000 |
| 200000 | 100000 | 50000 | 70000 | | | 50000 | 80000 | 40000 | 60000 |
| --- | --- | --- | --- |
| 70000 | 150000 | 200000 | 100000 | | 1 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 150000 | 25000 | 10000 | 5000 |
| 450000 | 15000 | 20000 | 30000 |
| 35000 | 35000 | 5000 | 10000 |
| 45000 | 20000 | 30000 | 80000 |
| 200000 | 100000 | 50000 | 70000 | | | Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 450000 | 15000 | 20000 | 30000 |
| 45000 | 20000 | 30000 | 80000 |
| 150000 | 25000 | 10000 | 5000 |
| 35000 | 35000 | 5000 | 10000 |
| 50000 | 80000 | 40000 | 60000 |
| 200000 | 100000 | 50000 | 70000 |
| 70000 | 150000 | 200000 | 100000 | | 0 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 150000 | 25000 | 10000 | 5000 |
| 450000 | 15000 | 20000 | 30000 |
| 35000 | 35000 | 5000 | 10000 |
| 45000 | 20000 | 30000 | 80000 |
| 200000 | 100000 | 50000 | 70000 | | | 50000 | 80000 | 40000 | 60000 |
| --- | --- | --- | --- |
| 70000 | 150000 | 200000 | 100000 | | 1 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 150000 | 25000 | 10000 | 5000 |
| 450000 | 15000 | 20000 | 30000 |
| 35000 | 35000 | 5000 | 10000 |
| 45000 | 20000 | 30000 | 80000 |
| 200000 | 100000 | 50000 | 70000 | | | 450000 | 15000 | 20000 | 30000 |
| --- | --- | --- | --- |
| 45000 | 20000 | 30000 | 80000 |
| 150000 | 25000 | 10000 | 5000 |
| 35000 | 35000 | 5000 | 10000 |
| 50000 | 80000 | 40000 | 60000 |
| 200000 | 100000 | 50000 | 70000 |
| 70000 | 150000 | 200000 | 100000 | | 0 |
| Real<br>Graph | Statistical<br>Methods | | | |
| --- | --- | --- | --- | --- |
| Power-law | Lognormal | Exponential | Pareto-Exp. | LNP | | | Monterey<br>nodes13.843<br>edges≈704K | LogL.<br>AIC<br>RSS | 8.75338e+04<br>1.75069e+05<br>3.05267e+02 | 7.83008e+04<br>1.56605e+05<br>2.07443e+00 | 7.78214e+04<br>1.55644e+05<br>4.86935e-01 | 7.76411e+04<br>1.55188e+05<br>3.43766e-01 | 7.76411e+04<br>1.55288e+05<br>2.59320e-01 |
| --- | --- | --- | --- | --- | --- | --- |
| SantaBarbara<br>nodes27.140<br>edges≈2M | LogL.<br>AIC<br>RSS | 1.80247e+05<br>3.60497e+05<br>4.38954e+02 | 1.63328e+05<br>3.26660e+05<br>5.81415e+00 | 1.61209e+05<br>3.22421e+05<br>7.31640e-01 | 1.60516e+05<br>3.21036e+05<br>3.37774e-01 | 1.61152e+05<br>3.22311e+05<br>6.10471e-01 |
| Egypt<br>nodes283K<br>edges≈11M | LogL.<br>AIC<br>RSS | 1.62073e+06<br>3.24148e+06<br>1.17928e+03 | 1.53376e+06<br>3.06754e+06<br>7.68335e+00 | 1.53832e+06<br>3.07664e+06<br>1.69934e+00 | 1.50289e+06<br>3.00579e+06<br>3.43834e-01 | 1.49892e+06<br>2.99785e+06<br>2.13671e-01 |
| LosAngeles<br>nodes572K<br>edges≈43M | LogL.<br>AIC<br>RSS | 3.81640e+06<br>7.63281e+06<br>1.74060e+03 | 3.45975e+06<br>6.91950e+06<br>8.60777e+00 | 3.44290e+06<br>6.88581e+06<br>1.50800e+00 | 3.42677e+06<br>6.85354e+06<br>8.55362e-01 | 3.41280e+06<br>6.82561e+06<br>5.02215e-01 |
| NewYork<br>nodes855K<br>edges≈66M | LogL.<br>AIC<br>RSS | 5.66194e+06<br>1.13239e+07<br>1.81230e+03 | 5.23512e+06<br>1.04702e+07<br>1.65956e+01 | 5.17802e+06<br>1.03560e+07<br>1.87038e+00 | 5.12808e+06<br>1.02561e+07<br>5.88628e-01 | 5.13177e+06<br>1.02635e+07<br>7.90849e-01 |
| ManhattanR.W.<br>nodes957K<br>edges≈80M | LogL.<br>AIC<br>RSS | 6.76810e+06<br>1.35362e+07<br>1.31910e+03 | 5.92193e+06<br>1.18438e+07<br>4.01862e+00 | 5.86365e+06<br>1.17273e+07<br>9.62000e-02 | 6.02838e+06<br>1.20567e+07<br>8.07448e+00 | 5.89459e+06<br>1.92208e+07<br>6.29269e-01 |
| London<br>nodes1.6M<br>edges≈118M | LogL.<br>AIC<br>RSS | 1.07131e+07<br>2.14262e+07<br>1.79927e+03 | 9.75799e+06<br>1.95159e+07<br>1.24657e+01 | 9.60413e+06<br>1.92082e+07<br>7.33091e-01 | 9.65522e+06<br>1.92104e+07<br>2.30840e-01 | 9.61043e+06<br>1.17892e+07<br>1.26502e+00 |
| Orkut<br>nodes3M<br>edges≈111M | LogL.<br>AIC<br>RSS | 1.81346e+07<br>3.62692e+07<br>1.94280e+03 | 1.63179e+07<br>3.26358e+07<br>2.41064e+00 | 1.62442e+07<br>3.24885e+07<br>3.75274e-01 | 1.61573e+07<br>3.23147e+07<br>2.95699e-01 | 1.61822e+07<br>3.23645e+07<br>4.16978e-01 | | 1 |
| Real<br>Graph | Statistical<br>Methods | | | |
| --- | --- | --- | --- | --- |
| Power-law | Lognormal | Exponential | Pareto-Exp. | LNP | | | 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 |
| Real<br>Graph | Statistical<br>Methods | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Power-law | Lognormal | Exponential | Pareto-Exp. | LNP | | |
| Monterey<br>nodes13.843<br>edges≈704K | LogL.<br>AIC<br>RSS | 8.75338e+04<br>1.75069e+05<br>3.05267e+02 | 7.83008e+04<br>1.56605e+05<br>2.07443e+00 | 7.78214e+04<br>1.55644e+05<br>4.86935e-01 | 7.76411e+04<br>1.55188e+05<br>3.43766e-01 | 7.76411e+04<br>1.55288e+05<br>2.59320e-01 |
| SantaBarbara<br>nodes27.140<br>edges≈2M | LogL.<br>AIC<br>RSS | 1.80247e+05<br>3.60497e+05<br>4.38954e+02 | 1.63328e+05<br>3.26660e+05<br>5.81415e+00 | 1.61209e+05<br>3.22421e+05<br>7.31640e-01 | 1.60516e+05<br>3.21036e+05<br>3.37774e-01 | 1.61152e+05<br>3.22311e+05<br>6.10471e-01 |
| Egypt<br>nodes283K<br>edges≈11M | LogL.<br>AIC<br>RSS | 1.62073e+06<br>3.24148e+06<br>1.17928e+03 | 1.53376e+06<br>3.06754e+06<br>7.68335e+00 | 1.53832e+06<br>3.07664e+06<br>1.69934e+00 | 1.50289e+06<br>3.00579e+06<br>3.43834e-01 | 1.49892e+06<br>2.99785e+06<br>2.13671e-01 |
| LosAngeles<br>nodes572K<br>edges≈43M | LogL.<br>AIC<br>RSS | 3.81640e+06<br>7.63281e+06<br>1.74060e+03 | 3.45975e+06<br>6.91950e+06<br>8.60777e+00 | 3.44290e+06<br>6.88581e+06<br>1.50800e+00 | 3.42677e+06<br>6.85354e+06<br>8.55362e-01 | 3.41280e+06<br>6.82561e+06<br>5.02215e-01 |
| NewYork<br>nodes855K<br>edges≈66M | LogL.<br>AIC<br>RSS | 5.66194e+06<br>1.13239e+07<br>1.81230e+03 | 5.23512e+06<br>1.04702e+07<br>1.65956e+01 | 5.17802e+06<br>1.03560e+07<br>1.87038e+00 | 5.12808e+06<br>1.02561e+07<br>5.88628e-01 | 5.13177e+06<br>1.02635e+07<br>7.90849e-01 | | | ManhattanR.W.<br>nodes957K<br>edges≈80M | LogL.<br>AIC<br>RSS | 6.76810e+06<br>1.35362e+07<br>1.31910e+03 | 5.92193e+06<br>1.18438e+07<br>4.01862e+00 | 5.86365e+06<br>1.17273e+07<br>9.62000e-02 | 6.02838e+06<br>1.20567e+07<br>8.07448e+00 | 5.89459e+06<br>1.92208e+07<br>6.29269e-01 |
| --- | --- | --- | --- | --- | --- | --- |
| London<br>nodes1.6M<br>edges≈118M | LogL.<br>AIC<br>RSS | 1.07131e+07<br>2.14262e+07<br>1.79927e+03 | 9.75799e+06<br>1.95159e+07<br>1.24657e+01 | 9.60413e+06<br>1.92082e+07<br>7.33091e-01 | 9.65522e+06<br>1.92104e+07<br>2.30840e-01 | 9.61043e+06<br>1.17892e+07<br>1.26502e+00 |
| Orkut<br>nodes3M<br>edges≈111M | LogL.<br>AIC<br>RSS | 1.81346e+07<br>3.62692e+07<br>1.94280e+03 | 1.63179e+07<br>3.26358e+07<br>2.41064e+00 | 1.62442e+07<br>3.24885e+07<br>3.75274e-01 | 1.61573e+07<br>3.23147e+07<br>2.95699e-01 | 1.61822e+07<br>3.23645e+07<br>4.16978e-01 | | 1 |
| Real<br>Graph | Statistical<br>Methods | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Power-law | Lognormal | Exponential | Pareto-Exp. | LNP | | |
| Monterey<br>nodes13.843<br>edges≈704K | LogL.<br>AIC<br>RSS | 8.75338e+04<br>1.75069e+05<br>3.05267e+02 | 7.83008e+04<br>1.56605e+05<br>2.07443e+00 | 7.78214e+04<br>1.55644e+05<br>4.86935e-01 | 7.76411e+04<br>1.55188e+05<br>3.43766e-01 | 7.76411e+04<br>1.55288e+05<br>2.59320e-01 |
| SantaBarbara<br>nodes27.140<br>edges≈2M | LogL.<br>AIC<br>RSS | 1.80247e+05<br>3.60497e+05<br>4.38954e+02 | 1.63328e+05<br>3.26660e+05<br>5.81415e+00 | 1.61209e+05<br>3.22421e+05<br>7.31640e-01 | 1.60516e+05<br>3.21036e+05<br>3.37774e-01 | 1.61152e+05<br>3.22311e+05<br>6.10471e-01 |
| Egypt<br>nodes283K<br>edges≈11M | LogL.<br>AIC<br>RSS | 1.62073e+06<br>3.24148e+06<br>1.17928e+03 | 1.53376e+06<br>3.06754e+06<br>7.68335e+00 | 1.53832e+06<br>3.07664e+06<br>1.69934e+00 | 1.50289e+06<br>3.00579e+06<br>3.43834e-01 | 1.49892e+06<br>2.99785e+06<br>2.13671e-01 |
| LosAngeles<br>nodes572K<br>edges≈43M | LogL.<br>AIC<br>RSS | 3.81640e+06<br>7.63281e+06<br>1.74060e+03 | 3.45975e+06<br>6.91950e+06<br>8.60777e+00 | 3.44290e+06<br>6.88581e+06<br>1.50800e+00 | 3.42677e+06<br>6.85354e+06<br>8.55362e-01 | 3.41280e+06<br>6.82561e+06<br>5.02215e-01 |
| NewYork<br>nodes855K<br>edges≈66M | LogL.<br>AIC<br>RSS | 5.66194e+06<br>1.13239e+07<br>1.81230e+03 | 5.23512e+06<br>1.04702e+07<br>1.65956e+01 | 5.17802e+06<br>1.03560e+07<br>1.87038e+00 | 5.12808e+06<br>1.02561e+07<br>5.88628e-01 | 5.13177e+06<br>1.02635e+07<br>7.90849e-01 | | | 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 |
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