# A Data-Driven Approach to Discovering Process Choreography
## 6 Discussion
This situation may be because there was insufficient information for the representation obtained from the word embedding model to obtain a high similarity, making it difficult to relate all message-type events. * **Over-complete choreography**. This refers to the fact that the method finds part of the process's choreography but also recovers irrelevant relationships not found in the reference choreography. This behavior is because the information used to obtain the representation from the event logs is very general. The above issue causes more relationships to be recovered than the existing ones and to meet the condition that the calculated similarity value exceeds the threshold \(U_{a}\). * **Partially correct choreography**. This refers to the model identifying a percentage of the process choreography correctly. In addition, with the ability to find partially correct relationships; that is, in a relationship of two identified events \((a,b^{\prime})\), an event \(a\) or \(b^{\prime}\) is incorrect in the relationship, due to the relationship that is expected to be recovered, according to the reference model, whether \((a,c^{\prime})\) or \((e,b^{\prime})\). The above may be because the identified relationship \((a,b^{\prime})\) has a higher degree of similarity than the expected relationship \((a,c^{\prime})\) or \((e,b^{\prime})\). This behavior is caused by the fact that the information used to obtain the representation is not sufficiently discriminating to separate the relationships correctly and that the word-embedding model did not correctly learn from the information in the event logs, causing the generation of relationships with high similarity between message-type tasks and other event-types. In the experimentation carried out, the scenario with the greatest complexity in identifying message-type tasks was _Healthcare_, according to the weighted value of 0.54 in the _FsR_ metric. In the _Hethcare_ scenario, the process choreographies discovered had the characteristics of a _partially correct choreography_ and a _under-complete choreography_. In the _Air Quality System_ and _Travel Agency_ scenarios, the process choreographies were classified as a _complete choreography_, indicating that the information in the event logs, as well as the patterns defined in the proposed methodology, supported the construction of a process choreography similar to the expected one. Moreover, in the scenarios _Purchase order_ and _Manufacturing process_, process choreographies were generated with characteristics of _Complete choreography_ and _Over-complete choreography_, which indicates that the complete choreography was recovered but relationships that were not part of the choreography were also recovered, as seen in the \(RP\) metric of 0.83 and 0.91, respectively. Finally, in the _Transfer of goods_ scenario, choreographies with characteristics of _over-complete choreography_ and _under-complete choreography_ were obtained, which were reflected in the \(PR\) and \(RR\) metrics, indicating that true relations and relations that were not part of the choreography of the process were recovered.