# CONDA-PM--A Systematic Review and Framework for Concept Drift Analysis in Process Mining
## 7 CONDA-PM Application and Evaluation
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Publication**} & \multirow{2}{*}{**Tool Availability**} & \multicolumn{2}{c}{**Evaluation Input**} & \multirow{2}{*}{**Evaluation (What/How)**} \\ \cline{3-4} \cline{6-6}  & & **Artificial** & **Real-life** & \\ \hline \multirow{3}{*}{S1} & \multirow{3}{*}{prototype} & & log from the manufacturing & \multirow{3}{*}{the ability of the approach to identify drifts with different thresholds for outlier detection} \\  & & & & instances \& 40436 events \\ \hline \multirow{3}{*}{S2} & \multirow{3}{*}{Python implementation of the algorithms} & \multirow{3}{*}{four synthetic logs} & Italian IT help desk log & **what**: the ability to identify different drift types \& plotting drifts as charts \& maps \\  & & & \& BPTC’11 log & **How**: comparing the detection results to those in Reference [31] and computing F-scores \\ \hline \multirow{3}{*}{S3} & \multirow{3}{*}{a tool to synthesis process execution logs + a web service to transparent static logs into event streams + a web service to run algorithms on events} & Insurance process & \\  & & & augmented by cases & \\  & & & representing all types of & \\ \hline \multirow{3}{*}{S4} & \multirow{3}{*}{Multi Perspective Process Comparator MPC plugin in ProM} & \multirow{3}{*}{Insurance process augmented by cases representing all types of drifts} & \multirow{3}{*}{The ability of the proposed algorithms to detect the 4 types of drifts} \\  & & & & drifts \\ \cline{3-4}  & & & BPTC’13 \& BPTC’13 \& BPTC’13 \& **Compared to Process Comparator plugin** \\  & & & (cases of an IT incident) & **in ProM regardingdifferences at the event \\  & & & handling process at Vlov & level (intra-event \& inter-event relations) \\  & & & Belgium-IT teams are & -differences at the fragment level(intra-fragment organized into tech-wide & -differences at the fragment levels/time-fragment functions, organization lines & -differences at the fragment graphs)-time-wise differences compared to case-wise differences using a sliding window of 3 days. ** \\ \hline \multirow{3}{*}{S5} & \multirow{3}{*}{ProDrift as a plugin in Apromore platform} & \multirow{3}{*}{loan application (72 event logs [four for each of 18 change patterns]-15 activities in the base model)+18 logs for gradual drifts} & \multirow{3}{*}{motor insurance claims(4509 cases-29108 events)\(-\)motor insurance claims of different hazard (2577 cases-17474 events)} & \multirow{3}{*}{**Accuracy assessment using F-score \& mean delay-experiment validation of results on real-life logs What: impact of window size on accuracy \&**What**: impact of window size on accuracy \& impact of oscillation filter size-impact of adaptive window-accuracy per change pattern -time performance-comparison with results in Reference [13] \\ \hline \multirow{3}{*}{S6 \& S13} & \multirow{3}{*}{Trace Clustering package in ProM} & \multirow{3}{*}{ \begin{tabular}{} \end{tabular}  } & two logs (Dutch & **What**: Comparison to Trace Alignment& ActIracTrac \\  & & & hospital-1143 cases-624 activities-15029 events)+ & **How**: mining the model for each technique using Flexible heuristics Miner