# CvAMoS--Event Abstraction Using Contextual Information
## 5 Evaluation
### Evaluation on Synthetic Datasets  
The objective of the event abstraction is to recognize motifs referring to activities in a log, hence the first goal of the evaluation is to verify the performance of the algorithm in identifying a list of predefined patterns (i.e., RQ1). To accomplish this goal, we identified a series of eight patterns that both CvAMoS and LPM had to recognize. The patterns were devised starting from real behavior referring to possible human routines and patterns, followed by a careful scrutiny of existing datasets [22; 23] in order to find a match. For each pattern, we constructed an event log, composed of four traces and about 150 events. Each trace contains one or more sub-traces that match the pattern. The patterns are presented in Table 1, and a process model is drawn for each of them. Patterns P1, P2, P3, P6, P7, and P8 have an extended version that includes a noise activity in the corresponding sub-trace. The extra activity is added to test the algorithms' ability to handle noise when identifying a pattern. The second goal of the evaluation is to verify if the algorithm is able to deal with contextual variables (RQ1), i.e., to recognize motifs and distinguish them according to the state of the environment. To achieve the goal, we created a second version of the above-mentioned logs, which includes context. Each trace in the log contains multiple instances of the same pattern. The events related to the environment temperature are added to the event logs. The temperature is collected in the form of continuous measurements. In the first half of each trace, there are events related to a thermometer whose temperature is \begin{table}
\begin{tabular}{p{42.7 pt} p{284.5 pt}} \hline \hline
**Pattern** & **Explanation** \\ \hline P1 & A sensor is triggered several times in a row, meaning that a person is executing an activity for a certain amount of time and which is captured by a single sensor, e.g., \(\langle AAAAAA\rangle\). \\ \hline P2 & The pattern involves two sensors that are in sync, and thus alternating. Usually, sensors in close proximity are synchronized, e.g., a person is executing an activity in a limited space and causes the activation of two sensors, such as \(\langle AB\ AB\ AB\ AB\rangle\). \\ \hline P3 & The pattern involves two sensors, that are not in sync. The situation is the same as P2, but the sensors can trigger in any order, e.g., \(\langle AB\ BA\ BA\ AB\rangle\). \\ \hline P4 & The pattern involves several sensors and the execution starts and ends with the same being triggered. In between, any other sensor can be fired in any order, e.g., entering a room, moving, and leaving: the first and last triggers are door sensors, resulting in \(\langle A\ BCD\ A\rangle\). \\ \hline P5 & The pattern involves three sensors, that are in sync. The execution starts and ends with the same sensor, e.g., entering a room, executing an activity that involves two sensors, and leaving the room: \(\langle AA\ BCC\ AA\rangle\). \\ \hline P6 & The pattern involves a set of sensors. The set is limited, but there is no order. The situation is similar to P4, but without boundaries, e.g., \(\langle ABCDEFGH\rangle\). \\ \hline P7 & The pattern is composed of a movement in a direction and then backward, e.g., walking down a corridor and then coming back: \(\langle ABC\ CBA\rangle\). \\ \hline P8 & The pattern involves a constant sensor that is activated in sync with the alternation of others sensors, e.g., while executing two activities in parallel such as watching the television and moving around the room, \(\langle AB\ AC\ AD\ AE\rangle\). \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Set of patterns and corresponding explanation. 10 degrees, while in the second half, a thermometer continuously collects a temperature of 20 degrees. As a consequence, the algorithm should be able to identify the defined patterns under the two contextual perspectives. This last case is not compared to LPM, as LPM is not able to deal with the context.