# Using Conceptual Recurrence and Consistency Metrics for Topic Segmentation in Debate
## 8 Performance Comparison and Evaluation
### Experimental Results

Table 2: \(Pk\) and \(WD\) values of each similarity cohesion calculation method without applying debate consistency metrics of CSseg. \begin{table}
\begin{tabular}{c c c c} \hline  & \multicolumn{2}{c}{\(Pk\)} \\ \cline{2-4}  & **Basic Income** & **Military** & **SAT** \\ \hline Plane & 0.0656 & 0.1429 & 0.1554 \\ Line & **0.0474** & 0.1429 & 0.1554 \\ Point & 0.0729 & 0.1429 & 0.1577 \\ Plane + Line & **0.0474** & **0.1217** & **0.1371** \\ Plane + Point & 0.0656 & 0.1429 & **0.1371** \\ Line + Point & **0.0474** & **0.1217** & **0.1371** \\ Plane + Line + Point & **0.0474** & **0.1217** & 0.1463 \\ LCseg & 0.1057 & 0.1693 & 0.1714 \\ \hline \end{tabular}
\end{table} 
Table 3: CSseg \(Pk\) and \(WD\) values when applying the debate consistency metrics of other-continuity, self-continuity, chain of arguments and counterarguments, and topic guide of moderator. Table 5 shows the CSseg \(Pk\) and \(WD\) values with the weight of self-continuity set to 0.5. CSseg Line was the method that consistently and best derived the values of \(Pk\) and \(WD\) in the three debates. Table 6 shows the CSseg \(Pk\) and \(WD\) values with the weight of chain of arguments and counterarguments set to 2. None of the three debates consistently yielded the best values of \(Pk\) or \(WD\). \begin{table}
\begin{tabular}{c c c c} \hline  & \multicolumn{3}{c}{\(Pk\)} \\ \cline{2-4}  & **Basic Income** & **Military** & **SAT** \\ \hline Plane & **0.0693** & **0.1693** & 0.1554 \\ Line & 0.0802 & **0.1640** & **0.1371** \\ Point & 0.0802 & **0.1640** & 0.1463 \\ Plane + Line & **0.0693** & 0.1852 & 0.1646 \\ Plane + Point & **0.0693** & 0.1640 & 0.1554 \\ Line + Point & **0.0693** & 0.1852 & **0.1371** \\ Plane + Line + Point & **0.0693** & 0.1852 & 0.1646 \\ LCseg & 0.1057 & **0.1693** & 0.1714 \\ \hline \end{tabular}
\end{table} 
Table 4: CSseg \(Pk\) and \(WD\) values with the weight of other-continuity set to 2. \begin{table}
\begin{tabular}{c c c c} \hline  & \multicolumn{3}{c}{\(Pk\)} \\ \cline{2-4}  & **Basic Income** & **Military** & **SAT** \\ \hline Plane & **0.0693** & 0.1693 & **0.1371** \\ Line & **0.0693** & **0.1640** & **0.1371** \\ Point & **0.0693** & 0.1852 & 0.1463 \\ Plane + Line & **0.0693** & 0.1693 & 0.1554 \\ Line + Point & 0.0802 & 0.1852 & **0.1371** \\ Plane + Line + Point & **0.0693** & 0.1852 & 0.1646 \\ LCseg & 0.1057 & 0.1693 & 0.1714 \\ \hline \end{tabular}
\end{table} 
Table 5: CSseg \(Pk\) and \(WD\) values with the weight of self-continuity set to 0.5. Table 7 shows the CSseg \(Pk\) and \(WD\) values with the weight of topic guide of moderator set to 2. CSseg Line and Line + Point were the methods that consistently and best derived the values of \(Pk\) and \(WD\) for the three debates. In addition, when the weight of topic guide of moderator was set, it resulted in more topic segmentation points similar to the points aggregated by the subjects. Summarizing the experimental results, the cases with the lowest \(Pk\) and \(WD\) in the three debates were Plane + Line and Line + Point, to which all debate consistency metrics were applied, and Line and Line + Point, to which the topic guide of moderator was applied.