# CvAMoS--Event Abstraction Using Contextual Information
## 5 Evaluation
### Evaluation on a Real Dataset
Consequently, we focus the comparison only on the visualization of the obtained motifs/models. As mentioned above, the models obtained by LPM are short and difficult to interpret, while the motifs obtained by CvAMoS are more meaningful. For simplicity, only one clear example is reported in Figure 5. The figure compares a motif obtained by CvAMoS with the patterns obtained by LPM, referring to the \begin{table}
\begin{tabular}{l c c c} \hline \hline
**ID** & **Scarf-Plot** & **\# EVS Before** & **\# EVS Not Abstracted** & **\% Abstracted EVS** \\ \hline C4 & & 718 & 276 & 61.6\% \\ \hline C5 & & 2109 & 1652 & 21.7\% \\ \hline C6 & & 866 & 384 & 55.7\% \\ \hline C7 & & 813 & 411 & 49.4\% \\ \hline C8 & & 702 & 284 & 59.5\% \\ \hline C9 & & 782 & 308 & 60.6\% \\ \hline C10 & & 335 & 119 & 64.5\% \\ \hline C11 & & 647 & 246 & 62.0\% \\ \hline C12 & & 931 & 336 & 63.9\% \\ \hline C13 & & 841 & 340 & 59.6\% \\ \hline C14 & & 275 & 90 & 67.3\% \\ \hline C15 & & 365 & 147 & 59.7\% \\ \hline C16 & & 570 & 198 & 65.3\% \\ \hline C17 & & 319 & 117 & 63.3\% \\ \hline C18 & & 553 & 214 & 61.3\% \\ \hline \hline \end{tabular} Each activity identifier is represented by a different shade of purple. Yellow shadows represent abstracted motifs.  
\end{table} 
Table 5: CASAS dataset before and after abstraction. same behavior. Figure 5a shows a motif identified by CvAMoS, that can be explained as the behavior of going from the kitchen to the bedroom. The motif has a length of 12 and can be identified in 8 out of 15 traces, with one occurrence per trace. To make a fair analogy with the results obtained by LPM, we tried to reconstruct the same behavior using the obtained models. As highlighted in Figure 5b, none of the models covered the path between the two rooms, but only the alternation between three couples of sensors is identified. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Run ID** & **Motifs Verified** & **Time (ms)** \\ \hline conf1 & 37 & 34,714 \\ \hline conf2 & 9 & 26,945 \\ \hline conf3 & 1 & 35,080 \\ \hline conf4 & 23 & 31,702 \\ \hline conf5 & 5 & 26,520 \\ \hline conf6 & 28 & 26,601 \\ \hline conf7 & 2 & 26,677 \\ \hline conf8 & 3 & 13,948 \\ \hline conf9 & 100 & 10,792 \\ \hline conf10 & 2 & 19,458 \\ \hline conf11 & 442 & 16,110 \\ \hline conf12 & 7 & 25,207 \\ \hline conf13 & 2 & 18,949 \\ \hline conf14 & 2 & 22,433 \\ \hline conf15 & 47 & 24,468 \\ \hline conf16 & 16 & 26,584 \\ \hline conf17 & 1 & 25,848 \\ \hline conf18 & 11 & 25,995 \\ \hline conf19 & 1 & 18,761 \\ \hline conf20 & 57 & 10,017 \\ \hline conf21 & 2 & 6039 \\ \hline conf22 & 7 & 8694 \\ \hline conf23 & 3 & 17,204 \\ \hline conf24 & 15 & 31,006 \\ \hline conf25 & 7 & 15,599 \\ \hline conf26 & 2 & 13,793 \\ \hline conf27 & 41 & 12,599 \\ \hline \multicolumn{3}{c}{**Total time (ms)**} & 571,743 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Computation time for the experiments with CvAMoS. To summarize, the results obtained using a real dataset show that:  
* CvAMoS, after 27 iterations, abstracted 52% of the total original event log, with a maximum of 67.30% in C14 and a minimum of 21.7% in C5. * The abstraction is computationally faster compared to LPM: it took 9.5 min in total, with an average execution time of 21 s. LPM needed in total 19.5 min to execute. * The identified motifs appear to be meaningful and can be interpreted as higher level activities, i.e., they can explain and describe a behavior. An example is shown in Figure 5.