Abstract: A method for translating an unstructured existing process into a well-structured process model is provided. The method is executed by a generation engine implemented as a computer program within a computing environment. The method includes analyzing elements or relationships of the unstructured existing process to detect model violations. The model violations include when the elements or the relationships fail at least one model requirement. The method include generating feedback suggestion types corresponding to the model violations and providing the feedback suggestion types in a user interface to automatically resolve the model violations.

Abstract: A method is provided. The method is executed by a modeling engine implemented as a computer program within a computing environment. The method includes translating a pre-processed model based on an unstructured existing process into a patched process tree. The translating includes detecting, structuring, and translating rigids of the pre-processed model into corresponding process tree equivalent elements of the patched process tree.

Abstract: Systems and methods for inserting a new node in a process tree are provided. A process tree representing execution of a process is received. The process tree is traversed to identify a path of nodes. One or more candidate locations under each node of the path of nodes are determined for positioning a new node. A position score is determined for each of the one or more candidate locations for positioning the new node. The new node is inserted in the process tree at one or more of the one or more candidate locations based on the position scores. The process tree with the inserted new node is output.

Abstract: Systems and methods for generating names for portions, such as, e.g., subprocesses or variants, of a process model are provided. One or more prompts defining 1) instructions, 2) a textual description of a process model of a process, and 3) one or more portions of the process model are received. A name for each of the one or more portions of the process model is generated using a large language model based on the instructions. The name for each of the one or more portions of the process model is output.

Abstract: Systems and methods for generating a description of non-conformance using a large language model are provided. One or more prompts defining 1) instructions, 2) a textual description of a process model of a process, and 3) an instance of execution of the process are received. A description of non-conformance of the instance of execution to the process model is generated using a large language model based on the textual description of the process model and the instructions. The description of the non-conformance of the instance of execution to the process model is output.

Abstract: Systems and methods for determining whether activity names of a process satisfy a validation criteria are provided. One or more prompts defining 1) instructions, 2) activity name validation criteria, and 3) activity names of a process are received. It is determined whether the activity names satisfy the validation criteria using a large language model based on the instructions. Results of the determining are output.

Abstract: Systems and methods for generating a natural language representation of one or more steps to be performed by one or more RPA (robotic process automation) robots for performing an activity are provided. One or more prompts defining 1) instructions, 2) a description of a process, 3) a name of a source system from which the process was extracted, and 4) a name of an activity of the process are received. A natural language representation of one or more steps to be performed by one or more RPA (robotic process automation) robots for performing the activity is performed using a large language model based on the instructions, the description of the process, the name of the source system, and the name of the activity. The natural language representation of the one or more steps to be performed by the one or more RPA robots for performing the activity is output.

Abstract: Systems and methods for determining a mapping between activities are provided. One or more prompts defining 1) instructions and 2) activities executed during one or more instances of execution of a process are received. A mapping between one or more activities extracted from a process model of the process and one or more of the activities executed during the one or more instances of execution is determined using a large language model based on the instructions. The mapping is output.

Abstract: Systems and methods for object centric process mining are provided. Execution data of a process having a plurality of entities is received. A plurality of object networks representing relationships between objects of the plurality of entities are generated based on the execution data. A set of transitions is determined for each of the plurality of object networks. A process graph of execution of the process is generated based on the sets of transitions. The process graph is output.

Abstract: A method for translating an unstructured existing process into a well-structured process model is provided. The method is executed by a generation engine implemented as a computer program within a computing environment. The method includes analyzing elements or relationships of the unstructured existing process to detect model violations. The model violations include when the elements or the relationships fail at least one model requirement.

Abstract: A method is provided. The method is executed by a modeling engine implemented as a computer program within a computing environment. The method includes translating a pre-processed model based on an unstructured existing process into a patched process tree. The translating includes detecting, structuring, and translating rigids of the pre-processed model into corresponding process tree equivalent elements of the patched process tree.

Abstract: A method is provided. The method is executed by a dependency identification engine implemented as a computer program within a computing environment. The method includes generating a data structure that represents a recorded process by the dependency identification engine from data. The method includes identifying activities of the data structure, determining connectivity between the activities, and determining, based on the connectivity, eligible activity pairs from the activates by the dependency identification engine. The method includes extending, based on the data, the data structure with annotations that represent long-term dependencies between the activities and generating a visualization of the data structure with the annotations by the dependency identification engine.

Abstract: Systems and methods for object centric process mining are provided. Execution data of a process having a plurality of entities is received. A plurality of object networks representing relationships between objects of the plurality of entities are generated based on the execution data. A set of transitions is determined for each of the plurality of object networks. A process graph of execution of the process is generated based on the sets of transitions. The process graph is output.

Abstract: Systems and methods for generating a process tree of a process are provided. An event log of the process is received. It is determined whether a base case applies to the event log and, in response to determining that the base case applies to the event log, one or more nodes are added to the process tree. In response to determining that the base case does not apply to the event log, the event log is split into sub-event logs and one or more nodes are added to the process tree. The steps of determining whether a base case applies and splitting the event log are repeatedly performed for each respective sub-event log using the respective sub-event log as the event log until it is determined that the base case applies to the event log. The process tree is output. The process may be a robotic process automation process.

Abstract: Systems and methods for annotating exclusive-or nodes or the exclusive outgoing paths of a process model of a process are provided. A process model representing execution of a process is received. Exclusive-or blocks in the process model are identified. Attribute data relating to an exclusive outgoing path from an exclusive-or node in each of the identified exclusive-or blocks are identified. At least one of the exclusive-or node or the exclusive outgoing paths are annotated based on the attribute data. The annotated at least one of the exclusive-or node or the exclusive outgoing paths are output.

Abstract: Systems and methods for generating a process tree of a process are provided. An event log of execution of a process is received. User constraints on one or more activities of the process are received from a user. A process tree is generated from the event log based on the user constraints. The process tree is output. The user constraints comprise at least one of inclusion constraints defining one or more activities that must be represented in the process tree or exclusion constraints defining one or more activities that must not be represented in the process tree.

Abstract: Systems and methods for generating a process tree of a process are provided. An event log of execution of a process is received. User constraints on one or more activities of the process are received from a user. A process tree is generated from the event log based on the user constraints. The process tree is output.

Abstract: Systems and methods for splitting an event log into sub-event logs are provided. The event log of a process is received. An activity relation score for a parallel relationship operator is calculated for each respective pair of activities of a plurality of pairs of activities in the event log based on 1) a frequency of occurrence of a first activity of the respective pair of activities between occurrences of a second activity of the respective pair of activities and 2) a frequency of occurrence of the second activity between occurrences of the first activity. A cut location in the event log is determined based on the activity relation scores. The event log is split into the sub-event logs based on the cut location.

Abstract: Systems and methods for generating a process tree of a process are provided. An event log of the process is received. It is determined whether a base case applies to the event log and, in response to determining that the base case applies to the event log, one or more nodes are added to the process tree. In response to determining that the base case does not apply to the event log, the event log is split into sub-event logs based on a frequency of directly follows relations and a frequency of strictly indirectly follows relations for pairs of activities in the event log and one or more nodes are added to the process tree. The steps of determining whether a base case applies and splitting the event log are repeatedly performed for each respective sub-event log using the respective sub-event log as the event log until it is determined that the base case applies to the event log. The process tree is output. The process may be a robotic process automation process.

Abstract: Systems and methods for generating a process tree of a process are provided. An event log of the process is received. It is determined whether a base case applies to the event log and, in response to determining that the base case applies to the event log, one or more nodes are added to the process tree. In response to determining that the base case does not apply to the event log, the event log is split into sub-event logs and one or more nodes are added to the process tree. The steps of determining whether a base case applies and splitting the event log are repeatedly performed for each respective sub-event log using the respective sub-event log as the event log until it is determined that the base case applies to the event log. The process tree is output. The process may be a robotic process automation process.