# WIRE: A Weighted Item Removal Method for Unsupervised Rank Aggregation
## 5 Experiments
### Results and Discussion
\begin{table}
\begin{tabular}{l c c c c c c c c c} \hline \hline \hline  & \multicolumn{6}{c}{**Precision**} & \multicolumn{6}{c}{**NDCG**} \\ \cline{2-13}
**MOSO** & **MAP** & \multicolumn{2}{c}{**P@1**} & **P@2** & **P@3** & **P@4** & **P@5** & **N@1** & **N@2** & **N@3** & **N@4** & **N@5** \\ \hline Borda Count & 0.507 & 0.350 & 0.450 & 0.400 & 0.425 & 0.440 & 0.350 & 0.427 & 0.397 & 0.415 & 0.426 \\ CombMNZ & 0.508 & 0.350 & 0.450 & 0.400 & 0.425 & 0.440 & 0.350 & 0.427 & 0.397 & 0.415 & 0.426 \\ Condorcet & 0.512 & 0.450 & 0.500 & 0.483 & 0.463 & 0.490 & 0.450 & 0.489 & 0.480 & 0.466 & 0.484 \\ Copeland & 0.516 & 0.450 & 0.475 & 0.500 & 0.500 & 0.520 & 0.450 & 0.469 & 0.488 & 0.490 & 0.505 \\ Outranking & 0.507 & 0.350 & \begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**CTT22**} & \multirow{2}{*}{**MAP**} & \multicolumn{8}{c}{**Precision**} & \multicolumn{8}{c}{**NDCG**} \\ \cline{2-13}  & & **P@1** & **P@2** & **P@3** & **P@4** & **P@5** & **N@1** & **N@2** & **N@3** & **N@4** & **N@5** \\ \hline Borda Count & 0.380 & 0.760 & 0.710 & 0.707 & 0.690 & 0.684 & 0.560 & 0.557 & 0.566 & 0.558 & 0.556 \\ CombMNZ & 0.378 & 0.760 & 0.710 & 0.700 & 0.685 & 0.680 & 0.560 & 0.557 & 0.561 & 0.554 & 0.552 \\ Condorcet & 0.418 & 0.700 & 0.690 & 0.733 & 0.730 & 0.720 & 0.567 & 0.559 & 0.561 & 0.563 & 0.552 \\ Copeland & 0.418 & 0.720 & 0.780 & 0.780 & 0.795 & 0.764 & 0.567 & 0.559 & 0.561 & 0.563 & 0.552 \\ Outranking & 0.401 & 0.720 & 0.710 & 0.720 & 0.725 & 0.716 & 0.587 & 0.589 & 0.578 & 0.578 & 0.572 \\ MCI & 0.267 & 0.700 & 0.710 & 0.653 & 0.645 & 0.640 & 0.567 & 0.569 & 0.537 & 0.527 & 0.518 \\ MC4 & 0.133 & 0.240 & 0.220 & 0.207 & 0.195 & 0.180 & 0.227 & 0.206 & 0.184 & 0.173 & 0.159 \\ MCT & 0.294 & 0.720 & 0.710 & 0.653 & 0.685 & 0.680 & 0.315 & 0.569 & 0.564 & 0.527 & 0.552 \\ RRA & 0.411 & 0.740 & 0.760 & 0.740 & 0.730 & 0.728 & 0.647 & 0.652 & 0.632 & 0.612 & 0.605 \\ PRG & – & – & – & – & – & – & – & – & – & – & – \\ AAM & – & – & – & – & – & – & – & – & – & – \\ DIBRA & 0.422 & 0.700 & 0.690 & 0.733 & 0.725 & 0.708 & 0.567 & 0.559 & 0.564 & 0.564 & 0.546 \\ DIBRA-P & 0.422 & 0.720 & 0.700 & 0.733 & 0.725 & 0.708 & 0.560 & 0.565 & 0.564 & 0.560 & 0.542 \\ DIBRA-WIRE & 0.424 & 0.760 & 0.800 & 0.780 & 0.785 & 0.768 & 0.653 & 0.664 & 0.644 & 0.634 & 0.617 \\ \hline \multicolumn{13}{c}{**Precision**} & \multicolumn{8}{c}{**NDCG**} \\ \cline{2-13}
**NTDT23** & **MAP** & **P@1** & **P@2** & **P@3** & **P@4** & **P@5** & **N@1** & **N@2** & **N@3** & **N@4** & **N@5** \\ \hline Borda Count & 0.306 & 0.512 & 0.463 & 0.422 & 0.402 & 0.400 & 0.366 & 0.376 & 0.360 & 0.355 & 0.361 \\ CombMNZ & 0.300 & 0.512 & 0.463 & 0.423 & 0.390 & 0.390 & 0.366 & 0.376 & 0.360 & 0.350 & 0.357 \\ Condorcet & 0.355 & 0.659 & 0.537 & 0.520 & 0.470 & 0.434 & 0.596 & 0.491 & 0.467 & 0.455 & 0.436 \\ Copeland & 0.355 & 0.659 & 0.537 & 0.512 & 0.470 & 0.434 & 0.596 & 0.491 & 0.467 & 0.455 & 0.436 \\ Outranking & 0.348 & 0.585 & 0.524 & 0.480 & 0.476 & 0.444 & 0.460 & 0.453 & 0.425 & 0.426 & 0.415 \\ MC1 & 0.222 & 0.439 & 0.378 & 0.358 & 0.323 & 0.307 & 0.355 & 0.339 & 0.318 & 0.300 & 0.296 \\ MC4 & 0.304 & 0.610 & 0.561 & 0.504 & 0.445 & 0.410 & 0.547 & 0.513 & 0.467 & 0.436 & 0.419 \\ MCT & 0.253 & 0.439 & 0.444 & 0.388 & 0.373 & 0.307 & 0.375 & 0.359 & 0.324 & 0.311 & 0.296 \\ RRA & 0.355 & 0.634 & 0.585 & 0.504 & 0.470 & 0.434 & 0.592 & 0.529 & 0.466 & 0.447 & 0.432 \\ PRG & 0.308 & 0.512 & 0.488 & 0.439 & 0.402 & 0.385 & 0.366 & 0.395 & 0.374 & 0.363 & 0.358 \\ AAM & – & – & – & – & – & – & – & – & – & – \\ DIBRA & 0.356 & 0.659 & 0.537 & 0.504 & 0.457 & 0.434 & 0.575 & 0.472 & 0.451 & 0.439 & 0.431 \\ DIBRA-P & 0.355 & 0.659 & 0.549 & 0.504 & 0.457 & 0.434 & 0.575 & 0.482 & 0.453 & 0.441 & 0.434 \\ DIBRA-WIRE & 0.360 & 0.659 & 0.549 & 0.504 & 0.470 & 0.434 & 0.596 & 0.491 & 0.454 & 0.442 & 0.427 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance evaluation of various rank aggregation methods in the CTT22 and NTDT23 datasets.