CN116126929A - Collaborative process mining method and system with object as center - Google Patents
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Abstract
The invention discloses a collaborative process mining method and a collaborative process mining system taking an object as a center, comprising the following steps: 1) Acquiring a business process event log containing multiple objects; 2) Analyzing the direct following activity relation of the event log, and constructing a direct following activity relation diagram; 3) Analyzing the execution frequency, the average duration and the contained object group of each activity in the direct following activity relation diagram in a business process event log containing multiple objects; 4) Analyzing the number of the objects of the same type and the average duration of the flow transmitted between the flows by using the execution frequency of each activity, the contained object group and the starting time and the ending time of each activity in the business flow event log; 5) Integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and visualizing. The method breaks the limitation that the existing process mining technology cannot mine the process model from the business process event log containing multiple objects.
Description
Technical Field
The invention relates to the technical field of process mining, in particular to a collaborative process mining method and system taking an object as a center.
Background
Process mining is capable of extracting useful information from event log records commonly generated by modern information systems, and the technology provides a new means for process discovery, monitoring and improvement in various application fields. There is a fundamental assumption in existing process mining technology that event logs and process models are both generated based on a single case concept. However, there are complex interactions such as one-to-many and many-to-many in the object-oriented information systems such as ERP and CRM that are widely used at present, and there is no global single case concept in the business process. When existing process mining techniques are applied to these systems, an imposed case concept flattens complex relationships in the raw data, losing interactions between process instances, resulting in convergence and divergence problems. Therefore, there is an urgent need for an object-centric collaborative process mining method, so as to more fully mine interaction information between process instances, more intuitively describe a logical relationship between activities in an object-centric business process, and improve the readability and comprehensiveness of the object-centric collaborative business process.
Disclosure of Invention
The first objective of the present invention is to overcome the drawbacks and disadvantages of the prior art, and to provide an object-centric collaborative process mining method, which breaks the limitation that the existing process mining technology cannot mine a process model from a business process event log containing multiple objects, and solves the problem that the existing process mining technology can flatten multi-dimensional original data containing multiple instances in a multi-object-oriented information system.
A second object of the present invention is to provide an object-centric collaborative process mining system.
The first object of the invention is achieved by the following technical scheme: the collaborative process mining method with the object as the center comprises the following steps:
1) Obtaining basic data, namely a business process event log containing multiple objects;
2) Analyzing the direct following activity relation of the business process event log obtained in the step 1), and constructing a direct following activity relation diagram;
3) Analyzing the execution frequency, the average duration and the contained object group of each activity in the direct following activity relation diagram in a business process event log containing multiple objects;
4) Analyzing the number of the same type objects transferred between the processes and the average duration of the processes by using the execution frequency of each activity and the object group obtained in the step 3) and the starting time and the ending time of each activity in the business process event log;
5) Integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and visualizing.
Further, in step 1), the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, where such log is composed of a set of events representing operations, and does not require that the case concept be assumed for the whole process, and each event contains multiple attributes, where an activity, an occurrence time, an end time, and a reference object are basic attributes; each event can reference several objects, each object can also be referenced by several events.
Further, in step 2), the direct following activity relation of the business process event log obtained in step 1) is analyzed, and a direct following activity relation diagram is constructed, and the specific steps are as follows:
2.1 Taking a business process event log containing multiple objects as input, traversing the event log track, and acquiring a direct following activity relationship in the event log by using a formula (1);
wherein DFR_S (L) represents a set of direct-following active relationships of a business process event log L containing multiple objects, L represents a business process event log containing multiple objects, σ represents a trace in L, σ i The ith activity representing trajectory sigma, sigma i+1 I+1th activity representing the trajectory σ, |σ| represents the total number of activities in the trajectory σ;
the direct following activity relationship means that an adjacent relationship exists between activities;
2.2 Analyzing the direct following activity relation between the activities obtained in the step 2.1), and constructing a direct following activity relation diagram by connecting a plurality of activities with the direct following activity relation by using directed edges;
the direct following activity relation graph refers to a directed graph constructed according to the direct following activity relation among activities.
Further, in step 3), the execution frequency, average duration and contained object group of each activity in the direct following activity relationship diagram in the business process event log containing multiple objects are analyzed, and the specific steps are as follows:
3.1 Calculating the execution times of each activity in the direct following activity relation diagram obtained in the step 2) in a business process event log containing multiple objects, analyzing the starting time and the ending time when each activity is executed, and calculating the average duration of each activity in the whole process by using the formula (2);
wherein activity_average_time (m) represents the average duration of executing activity m, m represents activity in a business process event log containing multiple objects, i represents the execution sequence number of the activity, s [ i ] represents the start time of the ith execution of activity m, e [ i ] represents the end time of the ith execution of activity m, and n represents the execution times of activity m, namely the execution frequency;
3.2 Storing the number of executions of each activity and the average duration, i.e., (p, q), in the form of a binary group, where p represents the number of executions of activity m; q represents the average duration of activity m, i.e. activity_average_time (m);
3.3 Traversing all execution sequence numbers i of each activity according to the execution frequency n of each activity obtained in the step 3.1), and storing all objects referenced by the activity in a list l when each execution is performed i In the method, each list is used as an object group, and finally all the object groups are put into one list, namely, a business process event log L= [ L ] containing multiple objects 1 ,l 2 ,…,l n ]Wherein i is more than or equal to 1 and n is more than or equal to n.
Further, in step 4), the number of objects of the same type and the average duration of the flow transmitted between the flows are analyzed by using the execution frequency of each activity and the object group obtained in step 3), and the starting time and the ending time of each activity in the business flow event log, and the specific steps are as follows:
4.1 Analyzing how many object types are referenced by each activity and how many different objects are referenced by each object type according to the object groups contained in each activity obtained in the step 3.3);
4.2 According to the direct following activity relation between the activities obtained in the step 2.1) and the number of the types of the objects referenced by the activities obtained in the step 4.1), analyzing the number of the objects of the same type transmitted between the current activity and the subsequent activity;
4.3 After obtaining the execution frequency of each activity obtained in the step 3) and the starting time and the ending time of each activity in the business process event log obtained in the step 1), analyzing the average duration time among processes by using the formula (3) by utilizing the direct following activity relation among the activities obtained in the step 2.1);
in the formula, process_average_time (h) represents the average duration of executing process h, wherein process h is a process with j as a start activity and j+1 as an end activity, and j represents a multi-object-oriented business processThe j-th activity in the part log, i represents the execution sequence number of the flow, s j+1 [i]Represents the start time, e, of activity j+1 when the ith flow is performed j [i]The end time of the activity j when the ith flow is executed is represented, and n represents the number of executions of the flow h, that is, the execution frequency.
Further, in step 5), integrating information on the direct following activity relation graph to obtain and visualize the collaborative process model with the object as the center, and specifically comprising the following steps:
5.1 Acquiring a tuple comprising the execution frequency and the average duration of each activity according to the step 3.2), and adding the tuple to each activity node directly following the activity relation graph to represent the execution frequency and the average duration of the activity node in the whole flow;
5.2 Obtaining a list l of all object groups referenced by each activity according to step 3.3) i Adds it to the underside of each active node and lists all object groups with the symbol "{ }" i Included therein;
5.3 The number of the object types and the number of the objects of various types, which are obtained in the step 4.1) and are cited by each activity, are used as the left weight value of the directed edge in the direct following activity relation diagram, and the number of the objects of the same type, which are transmitted from the current activity to the subsequent activity, is marked;
5.4 Marking the average duration between the processes obtained in the step 4.3) on the right side of the directed edge in the direct following activity relation graph as the average duration of the process from the current activity to the subsequent activity;
5.5 One type of object corresponds to one type of line, and according to the different types of the cited objects, the following operations are carried out on the directed edges and the movable frames in the collaborative process model with the object as the center:
if an activity only refers to one type of object, a linear frame is used, and when the activity transmits the reference object of the object type to the next activity, a linear frame is also used by the directed edge;
if the activity refers to multiple types of objects, overlapping the activity frame by using multiple linear frames, wherein the linear type of the directed edge taking the activity as a starting point depends on the object type of the reference object transferred by the activity to the next activity;
5.6 Adding a start node and an end node at two sides of each active node in the collaborative process model with the object as a center, and performing corresponding operation on borders of the start node and the end node, wherein the two nodes represent whether the activity has an object type needing to be started or ended.
Further, the step 5.6) includes the steps of:
5.6.1 Obtaining the number of object types of each active reference and the number of objects of each object type reference according to the step 4.1);
5.6.2 Analyzing the object type and the object number transfer relation between the current activity and the subsequent activity, judging whether the current activity has the object type to start or end, calculating the number of the related object of the object type, adding a start node S or an end node E on two sides of the current activity if the current activity has the new object type to start or end, and marking the number of the object on the directed edge;
5.6.3 The frame of the starting node and the frame of the ending node and the directed edge taking the two nodes as the end points are operated, the line types of the used frame and the directed edge are consistent with the line types of the corresponding object types, and finally the visual object-centered collaborative flow model is obtained;
the object-centric collaborative process model refers to a weighted directed graph constructed according to a direct following activity relation among activities, but unlike a conventional weighted directed graph, an activity node of the object-centric collaborative process model comprises an activity name, a tuple formed by the execution frequency and average duration of the activity and a list formed by an object group referenced during each execution of the activity; the weight on the directed edge is divided into a left part and a right part, which respectively represent the number of the transferred objects of the same type and the average duration of the flow; judging whether a certain object type needs to be started or ended according to the number of the referenced objects by each activity, if the certain object type needs to be started or ended, connecting a starting node S or an ending node E at two sides of the activity, wherein the line types of the frames of the starting node and the ending node depend on the represented object type; if the activity references a plurality of objects of different types, the movable frames need to be overlapped by using the frames of the corresponding line types of the different object types.
The second object of the invention is achieved by the following technical scheme: the object-centric collaborative process mining system is used for realizing the above object-centric collaborative process mining method, and comprises the following steps:
the data acquisition module is used for acquiring a business process event log containing multiple objects; the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, wherein the log consists of a group of events representing operations, the whole process is not required to be assumed to be in a case concept, each event contains multiple attributes, wherein the activity, the occurrence time, the ending time and the reference object are basic attributes, each event can refer to a plurality of objects, and each object can also be referred to by a plurality of events;
the system comprises a direct following activity relation module, a direct following activity relation module and a direct following activity relation module, wherein the direct following activity relation module is used for analyzing the direct following activity relation among activities from a business process event log containing multiple objects and constructing a direct following activity relation graph;
the node information module is used for calculating the execution frequency, the average duration and the contained object group of each activity;
the weight information module is used for calculating left and right weights of directed edges from object groups and execution frequency of each activity;
and the visualization module is used for integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and outputting the collaborative process model in a visualized manner.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. according to the method, the event log is processed from the dimension of the object, and the limitation of modeling and mining the business process based on a single global case in the conventional process mining technology is broken through by combining the process mining method.
2. The method and the system for visualizing the multi-instance process model mined from the business process event log containing the multi-objects for the first time take the form of the collaborative process model with the objects as centers, are more beneficial to the readability and comprehensiveness of the business process containing the multi-objects, and are beneficial to the follow-up optimization and promotion of the business process containing the multi-objects.
3. The invention has wide use space in the mining of the business process model with the object as the center and has wide prospect in the mining of the business process model with the object as the center.
Drawings
FIG. 1 is a schematic diagram of the logic flow of the method of the present invention.
FIG. 2 is a schematic diagram of a business process event log containing multiple objects used in an embodiment of the present invention.
FIG. 3 is a diagram of a direct-following activity relationship constructed from a log used in accordance with an embodiment of the present invention.
FIG. 4 is a schematic diagram of a collaborative process model centered on an object initially mined from a log used in accordance with an embodiment of the present invention (including only the execution frequency, average duration, and set of objects involved in an activity).
FIG. 5 is a schematic diagram of a log used in accordance with an embodiment of the present invention after further refining the collaborative process model centered on the mined objects (with the addition of the number of referenced objects transferred between activities, the average duration between processes, etc.).
FIG. 6 is a schematic diagram of a visual output object-centric collaborative flow model.
FIG. 7 is a simplified schematic diagram of an object-centric collaborative flow model (object group without active references).
Fig. 8 is a diagram of a system architecture of the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples.
Example 1
As shown in fig. 1, the embodiment discloses a collaborative process mining method with an object as a center, which includes the following steps:
1) Obtaining basic data, namely a business process event log containing multiple objects, wherein the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, the log consists of a group of events representing operations, the whole process is not required to be supposed with a case concept, each event contains multiple attributes, and the activity (activity), the occurrence time (start_time), the end time (end_time) and the object type are basic attributes; each event may refer to several objects, and each object may also be referred to by several events.
The business process event log containing multiple objects used in this embodiment is shown in fig. 2, and includes six basic attributes, which respectively have the following meanings: project_id: item numbering; order_id: order number; supply_id: warehousing and numbering; activity: activity; start_time: a start time; end_time: the ending time, and the item number, the order number and the warehouse-in number are object type attributes, and comprise four additional attributes, and have the following meanings respectively: roll: a role; type: a type; quality: number of pieces; staff_number: number of staff.
2) Analyzing the direct following activity relation of the event log obtained in the step 1), and constructing a direct following activity relation diagram, wherein the specific steps are as follows:
2.1 Taking a business process event log containing multiple objects as input, traversing the event log track, and acquiring a direct following activity relationship in the event log by using a formula (1);
wherein DFR_S (L) represents a set of direct-following active relationships of a business process event log L containing multiple objects, L represents a business process event log containing multiple objects, σ represents a trace in L, σ i The ith activity representing trajectory sigma, sigma i+1 I+1th activity representing the trajectory σ, |σ| represents the total number of activities in the trajectory σ;
the direct following activity relationship means that an adjacent relationship exists between activities;
by adopting the steps, the direct following activity relation DFR_S (L) = { (project application, project approval), (project approval, order approval), (order approval, warehouse application), (warehouse application, warehouse approval), (warehouse application, high-level manager approval), (warehouse approval, high-level manager approval) in the business process event log containing multiple objects is obtained.
2.2 Analyzing the direct following activity relation between the activities obtained in the step 2.1), and constructing a direct following activity relation diagram by connecting a plurality of activities with the direct following activity relation by using directed edges;
the direct following activity relation graph is a directed graph constructed according to the direct following activity relation among activities;
by adopting the steps, the direct following activity relation diagram which is constructed according to the multi-object-oriented business process event log and shown in figure 3 is obtained.
3) The method comprises the following specific steps of analyzing the execution frequency, average duration and contained object group of each activity in the direct following activity relation diagram in a business process event log containing multiple objects:
3.1 Calculating the execution times of each activity in the direct following activity relation diagram obtained in the step 2) in a business process event log containing multiple objects, analyzing the starting time and the ending time when each activity is executed, and calculating the average duration of each activity in the whole process by using the formula (2);
wherein activity_average_time (m) represents the average duration of executing activity m, m represents activity in a business process event log containing multiple objects, i represents the execution sequence number of the activity, s [ i ] represents the start time of the ith execution of activity m, e [ i ] represents the end time of the ith execution of activity m, and n represents the execution times (i.e. execution frequency) of activity m;
3.2 Storing the number of executions of each activity and the average duration, i.e., (p, q), in the form of a binary group, where p represents the number of executions of activity m; q represents the average duration of activity m, i.e. activity_average_time (m);
by adopting the steps, each active binary group is obtained, which comprises the following contents: project application (2, 1d1 h); project approval (2, 1 h); order review (2, 2d14 h); order approval (2, 13 h); warehouse-in application (4, 1 h); warehouse-in approval (3, 1 h); advanced manager approval (2, 1 h).
3.3 Traversing all execution sequence numbers i of each activity according to the execution frequency n of each activity obtained in the step 3.1), and storing all objects referenced by the activity in a list l when each execution is performed i In the method, each list is used as an object group, and finally all the object groups are put into one list, namely, a business process event log L= [ L ] containing multiple objects 1 ,l 2 ,…,l n ]Wherein i is more than or equal to 1 and n is more than or equal to n.
By adopting the steps, the object group list L of each activity is obtained, which comprises the following contents: project application [ [ P ] 1 ],[P 2 ]]The method comprises the steps of carrying out a first treatment on the surface of the Project approval [ [ P ] 1 ],[P 2 ]]The method comprises the steps of carrying out a first treatment on the surface of the Order review [ [ P ] 1 ,O 1 ],[P 2 ,O 2 ]]The method comprises the steps of carrying out a first treatment on the surface of the Order approval [ [ O ] 1 ],[O 2 ]]The method comprises the steps of carrying out a first treatment on the surface of the Warehouse entry application [ [ O ] 1 ,S 1 ],[O 1 ,S 2 ],[O 2 ,S 1 ],[O 2 ,S 2 ]]The method comprises the steps of carrying out a first treatment on the surface of the Warehouse-in approval [ [ S ] 1 ],[S 3 ],[S 4 ]]The method comprises the steps of carrying out a first treatment on the surface of the Advanced manager approval [ [ S ] 2 ],[S 4 ]]。
4) Analyzing the number of the same type objects transferred between the processes and the average duration of the processes by using the execution frequency of each activity and the object group obtained in the step 3) and the starting time and the ending time of each activity in the business process event log, and specifically comprising the following steps:
4.1 Analyzing how many object types are referenced by each activity and how many different objects are referenced by each object type according to the object groups contained in each activity obtained in the step 3.3);
4.2 According to the direct following activity relation between the activities obtained in the step 2.1) and the number of the types of the objects and the number of the objects of various types referenced by the activities obtained in the step 4.1), analyzing the number of the objects of the same type transmitted between the current activity and the subsequent activity;
4.3 After obtaining the execution frequency of each activity obtained in the step 3) and the starting time and the ending time of each activity in the event log obtained in the step 1), analyzing the average duration time among the processes by using the formula (3) by utilizing the direct following activity relation among the activities obtained in the step 2.1);
in the formula, process_average_time (h) represents the average duration of executing process h, wherein process h is a process taking j as a start activity and j+1 as an end activity, j represents a jth activity in a multi-object-oriented business process event log, i represents the execution sequence number of the process, s j+1 [i]Represents the start time, e, of activity j+1 when the ith flow is performed j [i]Indicating the end time of activity j when the ith flow is executed, and n indicating the number of executions of flow h (i.e., execution frequency).
By adopting the steps, the number of the same type objects transmitted among the obtained processes and the average duration of the processes are as follows: project application-project approval: 2.sub.1d1h; project approval-order review: 2|23h; order review-order approval: 2|2d14h; order approval-warehouse entry application: 2|23h; warehouse-in application-warehouse-in approval: 3.15.7 h; warehouse entry application-advanced manager approval: 1|25h; warehouse entry approval-advanced manager approval: 1.sub.1d.
5) Integrating information on the direct following activity relation diagram to obtain a collaborative process model with an object as a center and visualizing, wherein the method comprises the following specific steps:
5.1 Acquiring a tuple comprising the execution frequency and the average duration of each activity according to the step 3.2), and adding the tuple to each activity node directly following the activity relation graph to represent the execution frequency and the average duration of the activity node in the whole flow;
5.2 Obtaining a list l of all object groups referenced by each activity according to step 3.3) i It is added below each active node and is denoted by the symbol "{ }",list all objects group l i Included therein;
by adopting the steps, a collaborative process model with the object as the center shown in fig. 4 is preliminarily obtained.
5.3 The number of the object types and the number of the objects of various types, which are obtained in the step 4.1) and are cited by each activity, are used as the left weight value of the directed edge in the direct following activity relation diagram, and the number of the objects of the same type, which are transmitted from the current activity to the subsequent activity, is marked;
5.4 Marking the average duration between the processes obtained in the step 4.3) on the right side of the directed edge in the direct following activity relation graph as the average duration of the process from the current activity to the subsequent activity;
5.5 One type of object corresponds to one type of line, and according to the different types of the cited objects, the following operations are carried out on the directed edges and the movable frames in the collaborative process model with the object as the center:
if an activity only refers to one type of object, a linear frame is used, and when the activity transmits the reference object of the object type to the next activity, a linear frame is also used by the directed edge;
if the activity refers to multiple types of objects, overlapping the activity frame by using multiple linear frames, wherein the linear type of the directed edge taking the activity as a starting point depends on the object type of the reference object transferred by the activity to the next activity;
by adopting the steps, a collaborative process model with the perfect object as the center is obtained as shown in fig. 5.
5.6 Adding a start node and an end node at two sides of each active node in the collaborative process model with the object as a center, and performing corresponding operation on borders of the start node and the end node, wherein the two nodes represent whether the activity has an object type needing to be started or ended or not, and the specific steps are as follows:
5.6.1 Obtaining the number of object types of each active reference and the number of objects of each object type reference according to the step 4.1);
5.6.2 Analyzing the object type and the object number transfer relation between the current activity and the subsequent activity, judging whether the current activity has the object type to start or end, calculating the number of the related object of the object type, adding a start node S or an end node E on two sides of the current activity if the current activity has the new object type to start or end, and marking the number of the object on the directed edge;
5.6.3 The frame of the starting node and the frame of the ending node and the directional edge taking the two nodes as the end points are operated, the line types of the frame and the directional edge used are consistent with the line types of the corresponding object types, and finally the visual object-centered collaborative flow model is obtained.
The object-centric collaborative process model refers to a weighted directed graph constructed according to a direct following activity relation among activities, but unlike a conventional weighted directed graph, an activity node of the object-centric collaborative process model comprises an activity name, a tuple formed by the execution frequency and average duration of the activity and a list formed by an object group referenced during each execution of the activity; the weight on the directed edge is divided into a left part and a right part, which respectively represent the number of the transferred objects of the same type and the average duration of the flow; judging whether a certain object type needs to be started or ended according to the number of the referenced objects by each activity, if the certain object type needs to be started or ended, connecting a starting node S or an ending node E at two sides of the activity, wherein the line types of the frames of the starting node and the ending node depend on the represented object type; if the activity references a plurality of objects of different types, the movable frames need to be overlapped by using the frames of the corresponding line types of the different object types.
With the above steps, an object-centric collaborative flow model as shown in FIG. 6 is visually output, which does not contain a simplified version of the object group as shown in FIG. 7.
Example 2
The embodiment discloses an object-centric collaborative process mining system for implementing the object-centric collaborative process mining method described in embodiment 1, as shown in fig. 8, the system includes the following functional modules:
the data acquisition module is used for acquiring a business process event log containing multiple objects; the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, wherein the log consists of a group of events representing operations, the whole process is not required to be assumed to be in a case concept, each event contains multiple attributes, wherein the activity, the occurrence time, the ending time and the reference object are basic attributes, each event can refer to a plurality of objects, and each object can also be referred to by a plurality of events;
the system comprises a direct following activity relation module, a direct following activity relation module and a direct following activity relation module, wherein the direct following activity relation module is used for analyzing the direct following activity relation among activities from a business process event log containing multiple objects, and initially constructing a direct following activity relation graph;
the node information module is used for calculating the execution frequency, the average duration and the contained object group of each activity;
the weight information module is used for calculating left and right weights of directed edges from object groups and execution frequency of each activity;
and the visualization module is used for integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and outputting the collaborative process model in a visualized manner.
The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.
Claims (8)
1. The collaborative process mining method with the object as the center is characterized by comprising the following steps:
1) Obtaining basic data, namely a business process event log containing multiple objects;
2) Analyzing the direct following activity relation of the business process event log obtained in the step 1), and constructing a direct following activity relation diagram;
3) Analyzing the execution frequency, the average duration and the contained object group of each activity in the direct following activity relation diagram in a business process event log containing multiple objects;
4) Analyzing the number of the same type objects transferred between the processes and the average duration of the processes by using the execution frequency of each activity and the object group obtained in the step 3) and the starting time and the ending time of each activity in the business process event log;
5) Integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and visualizing.
2. The object-centric collaborative process mining method according to claim 1, wherein: in step 1), the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, wherein the log consists of a group of events representing operations, no case concept is required to be assumed for the whole process, and each event contains multiple attributes, wherein the activity, the occurrence time, the ending time and the reference object are basic attributes; each event can reference several objects, each object can also be referenced by several events.
3. The object-centric collaborative process mining method according to claim 2, wherein: in step 2), analyzing the direct following activity relation of the business process event log obtained in step 1), and constructing a direct following activity relation graph, wherein the specific steps are as follows:
2.1 Taking a business process event log containing multiple objects as input, traversing the event log track, and acquiring a direct following activity relationship in the event log by using a formula (1);
wherein DFR_S (L) represents a set of direct-following active relationships of a business process event log L containing multiple objects, L represents a business process event log containing multiple objects, and σ represents a trace in L，σ i The ith activity representing trajectory sigma, sigma i+1 I+1th activity representing the trajectory σ, |σ| represents the total number of activities in the trajectory σ;
the direct following activity relationship means that an adjacent relationship exists between activities;
2.2 Analyzing the direct following activity relation between the activities obtained in the step 2.1), and constructing a direct following activity relation diagram by connecting a plurality of activities with the direct following activity relation by using directed edges;
the direct following activity relation graph refers to a directed graph constructed according to the direct following activity relation among activities.
4. The object-centric collaborative process mining method according to claim 3, wherein: in step 3), the execution frequency, the average duration and the contained object group of each activity in the direct following activity relation diagram in the business process event log containing multiple objects are analyzed, and the specific steps are as follows:
3.1 Calculating the execution times of each activity in the direct following activity relation diagram obtained in the step 2) in a business process event log containing multiple objects, analyzing the starting time and the ending time when each activity is executed, and calculating the average duration of each activity in the whole process by using the formula (2);
wherein activity_average_time (m) represents the average duration of executing activity m, m represents activity in a business process event log containing multiple objects, i represents the execution sequence number of the activity, s [ i ] represents the start time of the ith execution of activity m, e [ i ] represents the end time of the ith execution of activity m, and n represents the execution times of activity m, namely the execution frequency;
3.2 Storing the number of executions of each activity and the average duration, i.e., (p, q), in the form of a binary group, where p represents the number of executions of activity m; q represents the average duration of activity m, i.e. activity_average_time (m);
3.3 Traversing all execution sequence numbers i of each activity according to the execution frequency n of each activity obtained in the step 3.1), and storing all objects referenced by the activity in a list l when each execution is performed i In the method, each list is used as an object group, and finally all the object groups are put into one list, namely, a business process event log L= [ L ] containing multiple objects 1 ,l 2 ,…,l n ]Wherein i is more than or equal to 1 and n is more than or equal to n.
5. The object-centric collaborative process mining method according to claim 4, wherein: in step 4), the number of the same type of objects and the average duration of the process transmitted between the processes are analyzed by using the execution frequency of each activity and the object group obtained in step 3), and the starting time and the ending time of each activity in the business process event log, and the specific steps are as follows:
4.1 Analyzing how many object types are referenced by each activity and how many different objects are referenced by each object type according to the object groups contained in each activity obtained in the step 3.3);
4.2 According to the direct following activity relation between the activities obtained in the step 2.1) and the number of the types of the objects referenced by the activities obtained in the step 4.1), analyzing the number of the objects of the same type transmitted between the current activity and the subsequent activity;
4.3 After obtaining the execution frequency of each activity obtained in the step 3) and the starting time and the ending time of each activity in the business process event log obtained in the step 1), analyzing the average duration time among processes by using the formula (3) by utilizing the direct following activity relation among the activities obtained in the step 2.1);
in the formula, the process_average_time (h) represents the average duration of executing the process h, wherein the process h is a process taking j as a starting activity and j+1 as an ending activity, and j represents the j in the multi-object-oriented business process event logThe activities, i, represent the execution sequence number of the flow, s j+1 [i]Represents the start time, e, of activity j+1 when the ith flow is performed j [i]The end time of the activity j when the ith flow is executed is represented, and n represents the number of executions of the flow h, that is, the execution frequency.
6. The object-centric collaborative process mining method according to claim 5, wherein: in step 5), integrating information on the direct following activity relation diagram to obtain a collaborative process model with an object as a center and visualizing, wherein the method comprises the following specific steps:
5.1 Acquiring a tuple comprising the execution frequency and the average duration of each activity according to the step 3.2), and adding the tuple to each activity node directly following the activity relation graph to represent the execution frequency and the average duration of the activity node in the whole flow;
5.2 Obtaining a list l of all object groups referenced by each activity according to step 3.3) i Adds it to the underside of each active node and lists all object groups with the symbol "{ }" i Included therein;
5.3 The number of the object types and the number of the objects of various types, which are obtained in the step 4.1) and are cited by each activity, are used as the left weight value of the directed edge in the direct following activity relation diagram, and the number of the objects of the same type, which are transmitted from the current activity to the subsequent activity, is marked;
5.4 Marking the average duration between the processes obtained in the step 4.3) on the right side of the directed edge in the direct following activity relation graph as the average duration of the process from the current activity to the subsequent activity;
5.5 One type of object corresponds to one type of line, and according to the different types of the cited objects, the following operations are carried out on the directed edges and the movable frames in the collaborative process model with the object as the center:
if an activity only refers to one type of object, a linear frame is used, and when the activity transmits the reference object of the object type to the next activity, a linear frame is also used by the directed edge;
if the activity refers to multiple types of objects, overlapping the activity frame by using multiple linear frames, wherein the linear type of the directed edge taking the activity as a starting point depends on the object type of the reference object transferred by the activity to the next activity;
5.6 Adding a start node and an end node at two sides of each active node in the collaborative process model with the object as a center, and performing corresponding operation on borders of the start node and the end node, wherein the two nodes represent whether the activity has an object type needing to be started or ended.
7. The object-centric collaborative process mining method according to claim 6, wherein: said step 5.6) comprises the steps of:
5.6.1 Obtaining the number of object types of each active reference and the number of objects of each object type reference according to the step 4.1);
5.6.2 Analyzing the object type and the object number transfer relation between the current activity and the subsequent activity, judging whether the current activity has the object type to start or end, calculating the number of the related object of the object type, adding a start node S or an end node E on two sides of the current activity if the current activity has the new object type to start or end, and marking the number of the object on the directed edge;
5.6.3 The frame of the starting node and the frame of the ending node and the directed edge taking the two nodes as the end points are operated, the line types of the used frame and the directed edge are consistent with the line types of the corresponding object types, and finally the visual object-centered collaborative flow model is obtained;
the object-centric collaborative process model refers to a weighted directed graph constructed according to a direct following activity relation among activities, but unlike a conventional weighted directed graph, an activity node of the object-centric collaborative process model comprises an activity name, a tuple formed by the execution frequency and average duration of the activity and a list formed by an object group referenced during each execution of the activity; the weight on the directed edge is divided into a left part and a right part, which respectively represent the number of the transferred objects of the same type and the average duration of the flow; judging whether a certain object type needs to be started or ended according to the number of the referenced objects by each activity, if the certain object type needs to be started or ended, connecting a starting node S or an ending node E at two sides of the activity, wherein the line types of the frames of the starting node and the ending node depend on the represented object type; if the activity references a plurality of objects of different types, the movable frames need to be overlapped by using the frames of the corresponding line types of the different object types.
8. An object-centric collaborative process mining system configured to implement the object-centric collaborative process mining method of any one of claims 1-7, comprising:
the data acquisition module is used for acquiring a business process event log containing multiple objects; the business process event log containing multiple objects refers to activity execution information recorded in an information management system in a business process, wherein the log consists of a group of events representing operations, the whole process is not required to be assumed to be in a case concept, each event contains multiple attributes, wherein the activity, the occurrence time, the ending time and the reference object are basic attributes, each event can refer to a plurality of objects, and each object can also be referred to by a plurality of events;
the system comprises a direct following activity relation module, a direct following activity relation module and a direct following activity relation module, wherein the direct following activity relation module is used for analyzing the direct following activity relation among activities from a business process event log containing multiple objects and constructing a direct following activity relation graph;
the node information module is used for calculating the execution frequency, the average duration and the contained object group of each activity;
the weight information module is used for calculating left and right weights of directed edges from object groups and execution frequency of each activity;
and the visualization module is used for integrating information on the direct following activity relation diagram to obtain a collaborative process model with the object as the center and outputting the collaborative process model in a visualized manner.
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