# A Data-Driven Approach to Discovering Process Choreography
## 6 Discussion  
The approaches for discovering IOBP models and process choreography presented in [39; 40; 41] exhibited a similar objective to our proposal. In [39], the authors described the discovery of an IOBP model and the interaction of messages between the participants using a healthcare scenario, as used in our experimentation. Their experiment obtained values of 0.4 and 1.00 for the fitness and precision metrics, respectively, utilizing an extended version of the event log to identify messages between participants. For their part [40], the authors reported the discovery of an IOBP model using the same Healthcare scenario and an extended event log to manage the message data, reporting independent diagrams for the IOBP model and the choreography process discovered. In our experimentation, the quality assessment of the IOBP model of the healthcare scenario obtained a value of 1.00 for the precision and recall metrics. Furthermore, in the quality assessment of the discovery of the intra-organizational models that made up the IOBP model, values of 0.98 and 1.00 were achieved for the precision and recall, respectively. On the other hand, ref. [41] obtained results between 0.94 and 1.00 for the precision metric and 0.905 and 1.00 for the recall metric in their discovery of a collaborative model using a classic event log (BPIC 2012) in the process mining domain. In their approach, no additional information is required to determine which tasks can be correlated, applying a technique of adjacent activities, and identifying the minimum execution time between the tasks to assess their link. We presented an experiment with the event log of the Air Quality System scenario, which had characteristics and complexity similar to the BPIC 2012 event log. The results of the identification evaluation of the message task achieved a value of 1 for  
Figure 2: Comparison of the reference IOBP/process choreography model versus the discovered IOBP/process choreography model for the _travel agency_ scenario. the precision and recall metrics. In discovering the IOBP model, a precision of 1 and 0.99 for recall was obtained. Our approach demonstrated a high performance on most event logs considered in the experimentation, without including additional information in the event log to identify message-type tasks. In this way, the proposal to discover the choreography of a process in an inter-organizational collaboration environment is governed by a set of configurable methods. For example, the values of the variables \(U_{t}\) and \(U_{a}\) allow filtering cases with similar information and selecting events that are potentially considered message-type tasks, respectively. The _word embedding_ representation used to calculate cosine similarity at the case and event level is highly effective. However, it is limited to the quantity and quality of information within the event logs, to generate a robust model that allows the discovery of the choreography between the participants of an IOBP. Furthermore, the patterns established in Table 1, as well as the models of intra-organizational processes discovered by the Split-miner algorithm, were fundamental elements for identifying the subtype in the message-type tasks, enabling the discovery of the choreography of the process. According to the results obtained in the evaluation of the discovery of the choreography of the process (see Tables 3 and 4), the following classification can be defined based on the characteristics identified in the experimentation:  
* **Complete choreography**. This refers to the fact that the proposed approach can find the complete process choreography in an inter-organizational environment, with the same number and relationships as found in the reference choreography. In conclusion, case-level and event-level representations of the event log only allow the discovery of message-type events. * **Under-complete choreography**. This refers to an approach that has the ability to find a percentage of the relationships in the choreography of the process.